bluuebunny/crossref_metadata_2025 huggingface dataset:
Biomass-Derived Carbon Materials for Advanced Metal-Ion Hybrid Supercapacitors: A Step Towards More Sustainable Energy
Authors: Shah Syed Shaheen
Published: May 2024

Modern research has made the search for high-performance, sustainable, and efficient energy storage technologies a main focus, especially in light of the growing environmental and energy-demanding issues. This review paper focuses on the pivotal role of biomass-derived carbon (BDC) materials in the development of high-performance metal-ion hybrid supercapacitors (MIHSCs), specifically targeting sodium (Na)-, potassium (K)-, aluminium (Al)-, and zinc (Zn)-ion-based systems. Due to their widespread availability, renewable nature, and exceptional physicochemical properties, BDC materials are ideal for supercapacitor electrodes, which perfectly balance environmental sustainability and technological advancement. This paper delves into the synthesis, functionalization, and structural engineering of advanced biomass-based carbon materials, highlighting the strategies to enhance their electrochemical performance. It elaborates on the unique characteristics of these carbons, such as high specific surface area, tuneable porosity, and heteroatom doping, which are pivotal in achieving superior capacitance, energy density, and cycling stability in Na-, K-, Al-, and Zn-ion hybrid supercapacitors. Furthermore, the compatibility of BDCs with metal-ion electrolytes and their role in facilitating ion transport and charge storage mechanisms are critically analysed. Novelty arises from a comprehensive comparison of these carbon materials across metal-ion systems, unveiling the synergistic effects of BDCs’ structural attributes on the performance of each supercapacitor type. This review also casts light on the current challenges, such as scalability, cost-effectiveness, and performance consistency, offering insightful perspectives for future research. This review underscores the transformative potential of BDC materials in MIHSCs and paves the way for next-generation energy storage technologies that are both high-performing and ecologically friendly. It calls for continued innovation and interdisciplinary collaboration to explore these sustainable materials, thereby contributing to advancing green energy technologies.
Neurospora sp. Mediated Synthesis of Naringenin for the Production of Bioactive Nanomaterials
Authors: Salunkhe Jitendra Dattatray , Pulidindi Indra Neel , Patil Vikas Sambhaji , Patil Satish Vitthal
Published: May 2024

The application of Neurospora sp., a fungus that commonly thrives on complex agricultural and plant wastes, has proven successful in utilizing citrus peel waste as a source of naringin. A UV-Vis spectrophotometric method proved the biotransformation of naringin, with an absorption maximum (λmax) observed at 310 nm for the biotransformed product, naringenin (NAR). Further verification of the conversion of naringin was provided through thin layer chromatography (TLC). The Neurospora crassa mediated biotransformation of naringin to NAR was utilized for the rapid (within 5 min) synthesis of silver (Ag) and gold (Au) nanoconjugates using sunlight to accelerate the reaction. The synthesized NAR-nano Ag and NAR-nano Au conjugates exhibited monodispersed spherical and spherical as well as polygonal shaped particles, respectively. Both of the nanoconjugates showed average particle sizes of less than 90 nm from TEM analysis. The NAR-Ag and NAR-Au nanoconjugates displayed potential enhancement of the antimicrobial activities, including antibacterial and nematicidal properties over either standalone NAR or Ag or Au NPs. This study reveals the potential of naringinase-producing Neurospora sp. for transforming naringin into NAR. Additionally, the resulting NAR-Ag and NAR-Au nanoconjugates showed promise as sustainable antibiotics and biochemical nematicides.
Bone Bruises and Concomitant Meniscus and Cartilage Damage in Anterior Cruciate Ligament Injuries: A Systematic Review and Meta-Analysis
Authors: Sohn Sueen , AlShammari Saad Mohammed , Lee Jeong Han , Kim Man Soo
Published: May 2024

(1) Background: Bone bruises in acute anterior cruciate ligament (ACL) injuries are closely linked to the occurrence of simultaneous meniscal and cartilage damage. Despite the frequent occurrence of associated injuries including bone bruises, meniscus, and cartilage damage in patients with ACL injuries, a systematic review of the relationships between the presence of bone bruises and the extent of meniscus and cartilage injuries has yet to be conducted. (2) Methods: Multiple comprehensive databases, including MEDLINE, EMBASE, and the Cochrane Library, were searched for studies that evaluated the relationship between bone bruises and meniscus or cartilage injuries following ACL injuries. Study selection, data extraction, and meta-analysis were performed. The Methodological Index for Non-Randomized Studies (MINORS) was used for quality assessments, and Review Manager 5.3 was used for data analysis. (3) Results: Data were extracted from 22 studies encompassing a total of 2891 patients with ACL injuries. Among the included studies, six studies investigated the relationships between bone bruises and medial meniscus (MM) or lateral meniscus (LM) injuries, while three studies investigated the relationships between bone bruises and cartilage injuries. There were no significant correlations between the presence of bone bruises and MM injuries (relative risk (RR) = 1.32; p = 0.61). A quantitative analysis indicated that individuals with bone bruises had a 2.71-fold higher likelihood of sustaining LM injuries than those without bone bruises (RR = 2.71; p = 0.0003). The analysis confirmed a significant relationship between bone bruises and cartilage injuries (RR = 6.18; p = 0.003). (4) Conclusions: Bone bruises occur most frequently in the lateral compartment. Bone bruises resulting from ACL injuries are related to accompanying LM injuries and cartilage injuries. Knowing these associations and the frequency of injuries may allow orthopedic surgeons to promptly address ACL-related meniscus and cartilage injuries on MRI results and in future clinical practice.
Synergistic Antibacterial Properties of Silver Nanoparticles and Its Reducing Agent from Cinnamon Bark Extract
Authors: Granja Alvear Araceli , Pineda-Aguilar Nayely , Lozano Patricia , Lárez-Velázquez Cristóbal , Suppan Gottfried , Galeas Salomé , Debut Alexis , Vizuete Karla , De Lima Lola , Saucedo-Vázquez Juan Pablo , Alexis Frank , López Floralba
Published: May 2024

Synthesis of silver nanoparticles with antibacterial properties using a one-pot green approach that harnesses the natural reducing and capping properties of cinnamon (Cinnamomum verum) bark extract is presented in this work. Silver nitrate was the sole chemical reagent employed in this process, acting as the precursor salt. Gas Chromatography-Mass Spectroscopy (GC-MS), High-Performance Liquid Chromatography (HPLC) analysis, and some phytochemical tests demonstrated that cinnamaldehyde is the main component in the cinnamon bark extract. The resulting bio-reduced silver nanoparticles underwent comprehensive characterization by Ultraviolet–Vis (UV-Vis) and Fourier Transform InfraRed spectrophotometry (FTIR), Dynamic Light Scattering (DLS), Transmission Electron Microscopy, and Scanning Electron Microscopy suggesting that cinnamaldehyde was chemically oxidated to produce silver nanoparticles. These cinnamon-extract-based silver nanoparticles (AgNPs-cinnamon) displayed diverse morphologies ranging from spherical to prismatic shapes, with sizes spanning between 2.94 and 65.1 nm. Subsequently, the antibacterial efficacy of these nanoparticles was investigated against Klebsiella, E. Coli, Pseudomonas, Staphylococcus aureus, and Acinetobacter strains. The results suggest the promising potential of silver nanoparticles obtained (AgNPs-cinnamon) as antimicrobial agents, offering a new avenue in the fight against bacterial infections.
In Search of Better Peptide-(Derived from PD-L2)-Based Immune Checkpoint Inhibitors
Authors: Klebansky Boris , Backer Marina , Gorbatyuk Vitaliy , Vinogradova Olga , Backer Joseph
Published: May 2024

Current anti-cancer immune checkpoint therapy relies on antibodies that primarily target the PD-1/PD-L1(-L2) negative regulatory pathway. Although very successful in some cases for certain cancers, these antibodies do not help most patients who, presumably, should benefit from this type of therapy. Therefore, an unmet clinical need for novel, more effective drugs targeting immune checkpoints remains. We have developed a series of high-potency peptide inhibitors interfering with PD-1/PD-L1(-L2) protein–protein interaction. Our best peptide inhibitors are 12 and 14 amino acids long and show sub-micromolar IC50 inhibitory activity in the in vitro assay. The positioning of the peptides within the PD-1 binding site is explored by extensive modeling. It is further supported by 2D NMR studies of PD-1/peptide complexes. These results reflect substantial progress in the development of immune checkpoint inhibitors using peptidomimetics.
Dual-Ring SNAREpin Machinery Tuning for Fast Synaptic Vesicle Fusion
Authors: Caruel Matthieu , Pincet Frédéric
Published: May 2024

During neurotransmission, neurotransmitters are released less than a millisecond after the arrival of the action potential. To achieve this ultra-fast event, the synaptic vesicle must be pre-docked to the plasma membrane. In this primed state, SNAREpins, the protein-coiled coils whose assembly provides the energy to trigger fusion, are partly zippered and clamped like a hairpin and held open and ready to snap close when the clamp is released. Recently, it was suggested that three types of regulatory factors, synaptophysin, synaptotagmins, and complexins act cooperatively to organize two concentric rings, a central and a peripheral ring, containing up to six SNAREpins each. We used a mechanical model of the SNAREpins with two separate states, half-zippered and fully zippered, and determined the energy landscape according to the number of SNAREpins in each ring. We also performed simulations to estimate the fusion time in each case. The presence of the peripheral SNAREpins generally smoothens the energy landscape and accelerates the fusion time. With the predicted physiological numbers of six central and six peripheral SNAREpins, the fusion time is accelerated at least 100 times by the presence of the peripheral SNAREpins, and fusion occurs in less than 10 μs, which is well within the physiological requirements.
Assessing the Effectiveness of Eslicarbazepine Acetate in Reducing Audiogenic Reflex Seizures in the GASH/Sal Model of Epilepsy
Authors: Gonçalves-Sánchez Jaime , Ramírez-Santos Thomas , López Dolores E. , Gonçalves-Estella Jesús M. , Sancho Consuelo
Published: May 2024

Eslicarbazepine acetate (ESL) is a third-generation antiepileptic drug indicated as monotherapy for adults with newly diagnosed epilepsy and as adjunctive therapy for the treatment of partial seizures. Our aim was to assess the effectiveness and safety of both acute and repeated ESL administration against reflex audiogenic seizures, as shown by the Genetic Audiogenic Seizures Hamster from Salamanca (GASH/Sal). Animals were subject to the intraperitoneal administration of ESL, applying doses of 100, 150 and 200 mg/kg for the acute study, whereas a daily dose of 100 mg/kg was selected for the subchronic study, which lasted 14 days. In both studies, the anticonvulsant effect of the therapy was evaluated using neuroethological methods. To assess the safety of the treatment, behavioral tests were performed, hematological and biochemical liver profiles were obtained, and body weight was monitored. In addition, the ESL levels in blood were measured after the acute administration of a 200 mg/kg dose. Treatment with ESL caused a reduction in seizure severity. No statistically significant differences were detected between the selected doses or between the acute or repeated administration of the drug. To summarize, the intraperitoneal administration of ESL is safe and shows an anticonvulsant effect in the GASH/Sal.
An Assessment of Semaglutide Safety Based on Real World Data: From Popularity to Spontaneous Reporting in EudraVigilance Database
Authors: Butuca Anca , Dobrea Carmen Maximiliana , Arseniu Anca Maria , Frum Adina , Chis Adriana Aurelia , Rus Luca Liviu , Ghibu Steliana , Juncan Anca Maria , Muntean Andrei Catalin , Lazăr Antonina Evelina , Gligor Felicia Gabriela , Morgovan Claudiu , Vonica-Tincu Andreea Loredana
Published: May 2024

Some glucagon-like peptide-1 receptor agonists (GLP-1 RAs), first used in the treatment of type 2 diabetes mellitus (T2DM), have been approved for the treatment of obesity in patients with or without T2DM (liraglutide—LIR, semaglutide—SEM, and tirzepatide—TIR). Social media had an important influence on the off-label use of GLP-1 RAs for obesity, especially for SEM. We analyzed the Google queries related to SEM to assess people’s interest in this drug. We also investigated the occurrence of adverse drug reactions (ADRs) by searching the EudraVigilance database (EV) for Individual Case Safety Reports (ICSRs) that reported SEM as the suspected drug and performed a descriptive and a disproportionality analysis. The data obtained for SEM were compared to other GLP-1 RAs. SEM had the highest proportions of searches on Google associated with the term “weight loss” and presented the lowest number of severe ADRs, but it also had the highest number of ICSRs reported in EV. Even though no unexpected safety issues have been reported for it until now, SEM has a hi3gh tendency for overdose reports. The most frequent off-label use was reported for SEM and TIR. In order to lower the risks of ADRs, the off-label use should be reduced and carefully monitored.
Exploring the Role of Guanylate-Binding Protein-2 in Activated Microglia-Mediated Neuroinflammation and Neuronal Damage
Authors: You Ji-Eun , Kim Eun-Ji , Kim Ho Won , Kim Jong-Seok , Kim Kyunggon , Kim Pyung-Hwan
Published: May 2024

Neuron damage by microglia, which act as macrophage cells in the brain, can result in various brain diseases. However, the function of pro-inflammatory or anti-inflammatory microglia in the neurons remains controversial. Guanylate-binding protein-2 (GBP2) is expressed and activated in the microglia in the early phase of the inflammatory response and plays an important role in controlling immune responses. In this study, we evaluated whether GBP2 initially reduces the immune response induced by microglia, and whether microglia induce pro-inflammatory functions in neurons via GBP2 expression. In lipopolysaccharide (LPS)-stimulated microglia, we assessed the expression of GBP2 and how it affects neurons via activated microglia. The biological functions of microglia due to the downregulation of the GBP2 gene were examined using short hairpin RNA (shRNA)-RNA-GBP2. Downregulated GBP2 affected the function of mitochondria in the microglia and showed reduced neuronal damage when compared to the control group in the co-culture system. Furthermore, this protein was observed to be highly expressed in the brains of dementia mice. Our results are the first to report that the downregulation of GBP2 in activated microglia has an anti-inflammatory function. This study suggests that the GBP2 gene can be used as a therapeutic target biomarker for inflammation-related neurodegenerative diseases.
Anterior Esthetic Restorations with the Stratified Stamp Technique: A Case Report
Authors: D’Arcangelo Camillo , Buonvivere Matteo , De Angelis Francesco
Published: May 2024

Anterior teeth restoration represents a challenge for dentists, who often rely on the dental technician’s wax-up. The proposed Stratified Stamp Technique (SST) allows for clinically reproducing the wax-up in a quick and easy way. A patient with fractures and discoloration on the upper central incisors was treated with resin-based composite direct restorations. Using SST, a 1 mm thick thermoformed polyethylene-terephthalate-glycol (PETG) template, based on the technician’s wax-up, was produced. Enamel Selective Area Reduction (SAR) was performed to guarantee adequate space for the restorations, and the fracture margins were rounded and finished. Traditional layering procedures according to the five color dimensions of teeth were performed, except for the final labial layer, which was realized with warm composite loaded inside the template and polymerized through it, in order to ensure accurate tooth morphology reproduction. SST offers a reliable method for transferring technician’s wax-up morphology to direct composite restorations in anterior teeth. Compared with other methods, SST allows for better isolation with a rubber dam and permits traditional layering with multiple composite shades, thus leading to satisfactory esthetic outcomes.
Pectoral Fin Propulsion Performance Analysis of Robotic Fish with Multiple Degrees of Freedom Based on Burst-and-Coast Swimming Behavior Stroke Ratio
Authors: Li Zonggang , Li Bin , Li Haoyu , Xia Guangqing
Published: May 2024

The pectoral fin propulsion of a bionic robotic fish always consists of two phases: propulsion and recovery. The robotic fish moves in a burst-and-coast swimming manner. This study aims to analyze a pair of bionic robotic fish with rigid pectoral fin propulsion with three degrees of freedom and optimize the elliptical propulsion curve with the minimum recovery stroke resistance using computational fluid dynamics methods. Then, the time allocated to the propulsion and recovery phases is investigated to maximize the propulsion performance of the bionic robotic fish. The numerical simulation results show that when the time ratio of the propulsion and recovery phases is 0.5:1, the resistance during the movement of the robotic fish is effectively reduced, and the drag-reducing effect is pronounced. According to a further analysis of pressure clouds and vortex structures, the pressure difference between the upstream and downstream fins of the pectoral fin varies with different stroke ratios. The increase in recovery phase time helps to prevent premature damage to the vortex ring structure generated during the propulsion process and improves propulsion efficiency.
Whale Optimization for Cloud–Edge-Offloading Decision-Making for Smart Grid Services
Authors: Arcas Gabriel Ioan , Cioara Tudor , Anghel Ionut
Published: May 2024

As IoT metering devices become increasingly prevalent, the smart energy grid encounters challenges associated with the transmission of large volumes of data affecting the latency of control services and the secure delivery of energy. Offloading computational work towards the edge is a viable option; however, effectively coordinating service execution on edge nodes presents significant challenges due to the vast search space making it difficult to identify optimal decisions within a limited timeframe. In this research paper, we utilize the whale optimization algorithm to decide and select the optimal edge nodes for executing services’ computational tasks. We employ a directed acyclic graph to model dependencies among computational nodes, data network links, smart grid energy assets, and energy network organization, thereby facilitating more efficient navigation within the decision space to identify the optimal solution. The offloading decision variables are represented as a binary vector, which is evaluated using a fitness function considering round-trip time and the correlation between edge-task computational resources. To effectively explore offloading strategies and prevent convergence to suboptimal solutions, we adapt the feedback mechanisms, an inertia weight coefficient, and a nonlinear convergence factor. The evaluation results are promising, demonstrating that the proposed solution can effectively consider both energy and data network constraints while enduring faster decision-making for optimization, with notable improvements in response time and a low average execution time of approximately 0.03 s per iteration. Additionally, on complex computational infrastructures modeled, our solution shows strong features in terms of diversity, fitness evolution, and execution time.
Development of a New Aggregation Method to Remove Nanoplastics from the Ocean: Proof of Concept Using Mussel Exposure Tests
Authors: Cid-Samamed Antonio , Nunes Catarina S. E. , Lomas Martínez Cristina , Diniz Mário S.
Published: May 2024

The overproduction and mismanagement of plastics has led to the accumulation of these materials in the environment, particularly in the marine ecosystem. Once in the environment, plastics break down and can acquire microscopic or even nanoscopic sizes. Given their sizes, microplastics (MPs) and nanoplastics (NPs) are hard to detect and remove from the aquatic environment, eventually interacting with marine organisms. This research mainly aimed to achieve the aggregation of micro- and nanoplastics (MNPs) to ease their removal from the marine environment. To this end, the size and stability of polystyrene (PS) MNPs were measured in synthetic seawater with the different components of the technology (ionic liquid and chitosan). The MPs were purchased in their plain form, while the NPs displayed amines on their surface (PS NP-NH2). The results showed that this technology promoted a significant aggregation of the PS NP-NH2, whereas, for the PS MPs, no conclusive results were found, indicating that the surface charge plays an essential role in the MNP aggregation process. Moreover, to investigate the toxicological potential of MNPs, a mussel species (M. galloprovincialis) was exposed to different concentrations of MPs and NPs, separately, with and without the technology. In this context, mussels were sampled after 7, 14, and 21 days of exposure, and the gills and digestive glands were collected for analysis of oxidative stress biomarkers and histological observations. In general, the results indicate that MNPs trigger the production of reactive oxygen species (ROS) in mussels and induce oxidative stress, making gills the most affected organ. Yet, when the technology was applied in moderate concentrations, NPs showed adverse effects in mussels. The histological analysis showed no evidence of MNPs in the gill’s tissues.
Ti3C2 Nanosheets Functionalized with Ferritin–Biomimetic Platinum Nanoparticles for Electrochemical Biosensors of Nitrite
Authors: Mu Rongqiu , Zhu Danzhu , Wei Gang
Published: May 2024

Nitrites widely exist in human life and the natural environment, but excessive contents of nitrites will result in adverse effects on the environment and human health; hence, sensitive and stable nitrite detection systems are needed. In this study, we report the synthesis of Ti3C2 nanosheets functionalized with apoferritin (ApoF)–biomimetic platinum (Pt) nanoparticle (Pt@ApoF/Ti3C2) composite materials, which were formed by using ApoF as a template and protein-inspired biomineralization. The formed nanohybrid exhibits excellent electrochemical sensing performance towards nitrite (NaNO2). Specifically, the Pt@ApoF catalyzes the conversion of nitrites into nitrates, converting the chemical signal into an electrical signal. The prepared Pt@ApoF/Ti3C2-based electrochemical NaNO2 biosensors demonstrate a wide detection range of 0.001–9 mM with a low detection limit of 0.425 μM. Additionally, the biosensors possess high selectivity and sensitivity while maintaining a relatively stable electrochemical sensing performance within 7 days, enabling the monitoring of NaNO2 in complex environments. The successful preparation of the Pt@ApoF/Ti3C2 nanohybrid materials provides a new approach for constructing efficient electrochemical biosensors, offering a simple and rapid method for detecting NaNO2 in complex environments.
Parkinson’s Disease Recognition Using Decorrelated Convolutional Neural Networks: Addressing Imbalance and Scanner Bias in rs-fMRI Data
Authors: Patil Pranita , Ford W. Randolph
Published: May 2024

Parkinson’s disease (PD) is a neurodegenerative and progressive disease that impacts the nerve cells in the brain and varies from person to person. The exact cause of PD is still unknown, and the diagnosis of PD does not include a specific objective test with certainty. Although deep learning has made great progress in medical neuroimaging analysis, these methods are very susceptible to biases present in neuroimaging datasets. An innovative decorrelated deep learning technique is introduced to mitigate class bias and scanner bias while simultaneously focusing on finding distinguishing characteristics in resting-state functional MRI (rs-fMRI) data, which assists in recognizing PD with good accuracy. The decorrelation function reduces the nonlinear correlation between features and bias in order to learn bias-invariant features. The publicly available Parkinson’s Progression Markers Initiative (PPMI) dataset, referred to as a single-scanner imbalanced dataset in this study, was used to validate our method. The imbalanced dataset problem affects the performance of the deep learning framework by overfitting to the majority class. To resolve this problem, we propose a new decorrelated convolutional neural network (DcCNN) framework by applying decorrelation-based optimization to convolutional neural networks (CNNs). An analysis of evaluation metrics comparisons shows that integrating the decorrelation function boosts the performance of PD recognition by removing class bias. Specifically, our DcCNN models perform significantly better than existing traditional approaches to tackle the imbalance problem. Finally, the same framework can be extended to create scanner-invariant features without significantly impacting the performance of a model. The obtained dataset is a multiscanner dataset, which leads to scanner bias due to the differences in acquisition protocols and scanners. The multiscanner dataset is a combination of two publicly available datasets, namely, PPMI and FTLDNI—the frontotemporal lobar degeneration neuroimaging initiative (NIFD) dataset. The results of t-distributed stochastic neighbor embedding (t-SNE) and scanner classification accuracy of our proposed feature extraction–DcCNN (FE-DcCNN) model validated the effective removal of scanner bias. Our method achieves an average accuracy of 77.80% on a multiscanner dataset for differentiating PD from a healthy control, which is superior to the DcCNN model trained on a single-scanner imbalanced dataset.
TSANN-TG: Temporal–Spatial Attention Neural Networks with Task-Specific Graph for EEG Emotion Recognition
Authors: Jiang Chao , Dai Yingying , Ding Yunheng , Chen Xi , Li Yingjie , Tang Yingying
Published: May 2024

Electroencephalography (EEG)-based emotion recognition is increasingly pivotal in the realm of affective brain–computer interfaces. In this paper, we propose TSANN-TG (temporal–spatial attention neural network with a task-specific graph), a novel neural network architecture tailored for enhancing feature extraction and effectively integrating temporal–spatial features. TSANN-TG comprises three primary components: a node-feature-encoding-and-adjacency-matrices-construction block, a graph-aggregation block, and a graph-feature-fusion-and-classification block. Leveraging the distinct temporal scales of features from EEG signals, TSANN-TG incorporates attention mechanisms for efficient feature extraction. By constructing task-specific adjacency matrices, the graph convolutional network with an attention mechanism captures the dynamic changes in dependency information between EEG channels. Additionally, TSANN-TG emphasizes feature integration at multiple levels, leading to improved performance in emotion-recognition tasks. Our proposed TSANN-TG is applied to both our FTEHD dataset and the publicly available DEAP dataset. Comparative experiments and ablation studies highlight the excellent recognition results achieved. Compared to the baseline algorithms, TSANN-TG demonstrates significant enhancements in accuracy and F1 score on the two benchmark datasets for four types of cognitive tasks. These results underscore the significant potential of the TSANN-TG method to advance EEG-based emotion recognition.
Research on the Decoupling Relationship and Driving Factors of Carbon Emissions in the Construction Industry of the East China Core Economic Zone
Authors: Zheng Simin , He Xiaorui , Liang Xian , Yu Liyan
Published: May 2024

This study focuses on the core economic zone of East China, utilizing the decoupling model to investigate the relationship between carbon emissions and economic development in the construction industry. Furthermore, it analyzes the driving factors through the application of the logarithmic mean index method. The findings reveal that, firstly, Zhejiang and Jiangsu provinces exhibit higher total carbon emissions in the construction industry. Except for Fujian Province, the other regions exhibit a downward trend after 2019. Secondly, there is considerable spatial variability in carbon emissions in the construction industry within the core economic zone of East China, and it gradually decreases over the study period. While economically developed regions like Zhejiang and Jiangsu provinces tend to concentrate and consume more resources and energy, their impact on surrounding neighboring provinces or cities is relatively limited. Thirdly, carbon emissions from the construction industry in the core economic zone of East China show a development trend shifting from weak decoupling to strong decoupling, indicating a healthy growth in the construction industry. Specifically, different regions show different trends. Lastly, regarding influencing factors, the impact direction of carbon intensity on total carbon emissions shows instability. Energy intensity consistently exhibits inhibitory effects, and the economy and the population scale act as driving forces.
Calculation of Column Pile Heave in Deep Excavation Based on the Rebound–Recompression Method
Authors: Yang Kaiwen , Chen Yun , Li Zhuofeng
Published: May 2024

Excessive column pile heave may result in engineering disasters such as instability of retaining structures and cracking of existing engineering piles in deep excavations. However, factors such as support weight, changeable support restraint resistance, and soil disturbance at the bottom of the excavation are often ignored or simplified in existing calculation methods but have a significant impact on the calculation results. Based on field soil parameters obtained by the rebound–recompression method, a semi-analytical method is proposed for estimating column pile heaves in a deep excavation. This method considers the influence of soil disturbance, the weight of the retaining structure, and the changeable horizontal support restraint, making the calculation result more consistent with the realistic situation. This method can also be used to analyze load transfer between the pile and the surrounding soil. The rationality of this proposed calculation method is verified by measured data, where the variation in pile stress state during deep excavation is analyzed. Finally, a parametric study is conducted, and the results show that the excavation size and the excavation depth have a great influence. However, the heave is hardly affected by the value of the limit relative displacement. The use of long piles with small diameter and the method of small block excavation are effective means to control the column pile heave. When the excavation area is large or the effective pile length is short, the factor of the position of the column pile cannot be ignored.
Simulation Study on Student Residential Energy Use Behaviors: A Case Study of University Dormitories in Sichuan, China
Authors: Zhang Yingzi , Zhang Bo , Hou Jingwen
Published: May 2024

Studying the energy use behavior of occupants is crucial for accurately predicting building energy consumption. However, few studies have considered the impact of occupant behaviors on energy consumption in university dormitories. The objective of this study is to establish an agent-based model of energy consumption for university dormitories based on energy use behavior. The dormitories of a typical university in Sichuan, China, were subdivided into three clusters using a two-step cluster analysis. Subsequently, the energy use behaviors of occupants in each type of dormitory were characterized to establish a stochastic energy use behavior model. On the basis of the above, NETLOGO was used to construct an agent-based model for dormitories’ energy consumption to dynamically simulate energy use behavior. The accuracy of the model was verified by comparing the simulated values with the measured data. Finally, a building-energy-friendly retrofit scheme was proposed, and it was found that the optimized dormitory reduced energy consumption by 16.07%. Therefore, the results can provide information support for energy-saving decisions during the early design and retrofit phases of buildings. With the popularity of centralized supply, the research methodology may provide an extensive reference for energy management policies and sustainable strategies in the building sector.
Clinical Correlations between Serological Markers and Endometrial Cancer
Authors: Marin Alina-Gabriela , Filipescu Alexandru , Petca Răzvan , Vlădăreanu Radu , Petca Aida
Published: May 2024

Background: Endometrial cancer is associated with changes in blood cell counts and with high levels of inflammatory markers, thus reflecting the tumor’s impact on various biological processes and suggesting their potential as biomarkers for endometrial cancer diagnosis, prognosis, and treatment response. The neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and monocyte-to-lymphocyte ratio in peripheral blood sampled preoperatively from patients have been reported to be independently associated with the prognosis of different types of malignancies. Objectives: This study aimed to compare several blood markers—red blood cells, white blood cells, platelet parameters, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, monocyte-to-lymphocyte ratio, C-reactive protein, and fibrinogen—in patients with benign or malignant endometrial tumors. Material and methods: Our retrospective study included 670 patients (192 diagnosed with endometrial cancer and 478 with endometrial hyperplasia), and we compared the serological parameters discussed above with those sampled the day before surgery. Results: Analysis of complete blood count indices revealed no significant differences in red blood cell or total white blood cell parameters between the endometrial cancer group and the endometrial hyperplasia group. However, a distinct pattern emerged in the white blood cell differential. The endometrial cancer group showed a statistically significant decrease in lymphocyte count compared with the endometrial hyperplasia group. In contrast, the endometrial cancer group showed significantly higher mean platelet counts and increased mean platelet volume compared with controls. Furthermore, the endometrial cancer group demonstrated a marked inflammatory response, as evidenced by significantly elevated levels of C-reactive protein, fibrinogen, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and monocyte-to-lymphocyte ratio compared with the endometrial hyperplasia group. Conclusions: The current research revealed statistically significant differences in multiple serological biomarkers between the two groups. These findings support the initial hypothesis regarding the potential utility of these biomarkers in endometrial cancer diagnosis, prognosis, and treatment response, highlighting the existence of biomarkers affordable for analysis under any health system, regardless of the country’s level of development.
Clinical Consequences of Unreconstructed Pelvic Defect Caused by Osteosarcoma with Subsequent Progressive Scoliosis in a Pediatric Patient—Case Report
Authors: Zacha Sławomir , Kotrych Katarzyna , Zacha Wojciech , Biernawska Jowita , Ali Arkadiusz , Ciechanowicz Dawid , Ziętek Paweł , Kotrych Daniel
Published: May 2024

Osteosarcoma is the most common primary malignant bone tumor in children and adolescents. The standard and most effective treatment is wide resection of the tumor combined with neoadjuvant chemotherapy. Adolescent idiopathic scoliosis (AIS) is a genetically determined three-dimensional spinal deformity, which occurs in teenage patients and is mostly progressive. The basic management strategy is surgical treatment when the curve exceeds 50 degrees. However, the indications are different in oncologic patients. The aim of this study was to describe a case of adolescent scoliosis with osteosarcoma of the pelvis. The authors conducted a scoping review using PubMed and Embase to analyze the state of knowledge. The presented paper is the first report of pelvis osteosarcoma coexisting with adolescent idiopathic scoliosis. Treatment for this complex case finished with very good results, with no recurrence observed during the nine-year follow-up.
Play Nicely: Evaluation of a Brief Intervention to Reduce Physical Punishment and the Beliefs That Justify It
Authors: Nuñez-Talero Danna Valentina , González Martha Rocío , Trujillo Angela
Published: May 2024

The objective of this study was to assess the efficacy of the Play Nicely brief intervention in diminishing both the utilization of physical punishment and the beliefs that endorse such behavior among a sample of Colombian parents with children aged 2 to 6. Utilizing a quasi-experimental design, the research included pretest and posttest evaluations and involved both an intervention group (n = 37) and a control group (n = 29). The assessment tools used were a scale to measure beliefs about the positive impacts of physical punishment and the Physical Assault subscale of the Spanish version of the Conflict Tactics Scale Parent–Child (CTSPC). Parents participated in a single online session, which offered eight interactive options and lasted 10 min. The results highlighted a high prevalence of physical punishment within the sample (81.8%) and established statistically significant correlations between the justification of physical punishment and its actual use. Approximately one month following the intervention, there was a significant reduction in the employment of physical punishment among the intervention group (p = 0.009), and a notable decrease in the belief that “Punishment is the best alternative to control children’s behavior” (p = 0.010) was observed. Consequently, the Play Nicely intervention proved effective in curtailing the use of physical punishment among parents of young children, demonstrating both efficacy and cost-effectiveness within a brief timeframe.
Prevalence and Characteristics of Sleep Disorders in Children Aged 7–17: Insights from Parental Observations at the Dental Office
Authors: Diéguez-Pérez Montserrat , Burgueño-Torres Laura , Reichard-Monefeldt Guillermo , Tapia-Sierra Fanny Esther , Ticona-Flores Jesús Miguel
Published: May 2024

Sleep disorders (SD) in children is a topic of great relevance due to their impact on a child’s general health. This has led us to study their prevalence and the factors that disturb them in the developing population. Using a validated Likert-type questionnaire, different behaviors observed by the parents during the different phases of their children’s sleep were evaluated during the last 6 months. A total of 206 children between the ages of 7 and 17 who attended a dental office participated in the study. The prevalence of SD was 47.6%. There were no significant differences regarding the SD in relation to sex (p = 0.796). The mean total score for children aged 7 to 11 years old was 42.3 (±14.25) compared to 45.44 (±15.51) for the group consisting of children aged 12 to 17 years old, reporting a statistically significant difference among both age groups (p = 0.01). The most frequent disorder was related to initiating and maintaining sleep (64.9%) while the least prevalent were the respiratory sleep disorders (27.2%). Given the high prevalence of these disorders, it is necessary to intercept them during childhood and establish educational guidelines in this regard throughout primary care.
Assessment of Autoregulation of the Cerebral Circulation during Acute Lung Injury in a Neonatal Porcine Model
Authors: Memisoglu Asli , Hinton Martha , Elsayed Yasser , Graham Ruth , Dakshinamurti Shyamala
Published: May 2024

In neonates with acute lung injury (ALI), targeting lower oxygenation saturations is suggested to limit oxygen toxicity while maintaining vital organ function. Although thresholds for cerebral autoregulation are studied for the management of premature infants, the impact of hypoxia on hemodynamics, tissue oxygen consumption and extraction is not well understood in term infants with ALI. We examined hemodynamics, cerebral autoregulation and fractional oxygen extraction, as measured by near-infrared spectroscopy (NIRS) and blood gases, in a neonatal porcine oleic acid injury model of moderate ALI. We hypothesized that in ALI animals, cerebral oxygen extraction would be increased to a greater degree than kidney or gut oxygen extraction as indicative of the brain’s adaptive efforts to increase cerebral oxygen extraction at the expense of splanchnic end organs. Fifteen anesthetized, ventilated 5-day-old neonatal piglets were divided into moderate lung injury by treatment with oleic acid or control (sham injection). The degree of lung injury was quantified at baseline and after establishment of ALI by blood gases, ventilation parameters and calculated oxygenation deficit, hemodynamic indices by echocardiography and lung injury score by ultrasound. PaCO2 was maintained constant during ventilation. Cerebral, renal and gut oxygenation was determined by NIRS during stepwise decreases in inspired oxygen from 50% to 21%, correlated with PaO2 and PvO2; changes in fractional oxygen extraction (ΔFOE) were calculated from NIRS and from regional blood gas samples. The proportion of cerebral autoregulation impairment attributable to blood pressure, and to hypoxemia, was calculated from autoregulation nomograms. ALI manifested as hypoxemia with increasing intrapulmonary shunt fraction, decreased lung compliance and increased resistance, and marked increase in lung ultrasound score. Brain, gut and renal NIRS, obtained from probes placed over the anterior skull, central abdomen and flank, respectively, correlated with concurrent SVC (brain) or IVC (gut, renal) PvO2 and SvO2. Cerebral autoregulation was impaired after ALI as a function of blood pressure at all FiO2 steps, but predominantly by hypoxemia at FiO2 < 40%. Cerebral ΔFOE was higher in ALI animals at all FiO2 steps. We conclude that in an animal model of neonatal ALI, cerebrovascular blood flow regulation is primarily dependent on oxygenation. There is not a defined oxygenation threshold below which cerebral autoregulation is impaired in ALI. Cerebral oxygen extraction is enhanced in ALI, reflecting compensation for exhausted cerebral autoregulation due to the degree of hypoxemia and/or hypotension, thereby protecting against tissue hypoxia.
Absorption by a Layered Microbolometer Pixel’s Active Element
Authors: Bolakis Christos , Vazouras Christos N.
Published: May 2024

Microbolometer arrays, i.e., arrays of micro-scale pixels sensing temperature via resistance changes, have proven to be an effective basis for real-time imaging instrumentation in infrared as well as terahertz frequencies. In previous work, a design of THz and IR absorbing nano-laminates of dielectric and metal layers was studied. It was shown via numerical modeling that absorption may be maximized by appropriate choices of thickness, permittivity and conductivity. In this work, an analytical approach to the problem is formulated based on the standard recursive multiple reflection formulas for multi-layered planar structures. The results fully confirm and extend previous numerical work. A previous relationship between wavelength and silicon thickness for maximum absorption, derived numerically for specific parameter combinations, is now generalized in a parametric closed form. The method can be extended to include multiple lossy dielectric layers and may serve as a tool for optimizing the absorption characteristics of more complex layered absorbing structures. This could enhance the sensitivity of the detection scheme of interest, providing benefits in terms of cost, efficiency, precision, and adjustability.
Neural Architecture Comparison for Bibliographic Reference Segmentation: An Empirical Study
Authors: Cuéllar Hidalgo Rodrigo , Pinto Elías Raúl , Torres-Moreno Juan-Manuel , Vergara Villegas  Osslan Osiris , Reyes Salgado Gerardo , Magadán Salazar Andrea
Published: May 2024

In the realm of digital libraries, efficiently managing and accessing scientific publications necessitates automated bibliographic reference segmentation. This study addresses the challenge of accurately segmenting bibliographic references, a task complicated by the varied formats and styles of references. Focusing on the empirical evaluation of Conditional Random Fields (CRF), Bidirectional Long Short-Term Memory with CRF (BiLSTM + CRF), and Transformer Encoder with CRF (Transformer + CRF) architectures, this research employs Byte Pair Encoding and Character Embeddings for vector representation. The models underwent training on the extensive Giant corpus and subsequent evaluation on the Cora Corpus to ensure a balanced and rigorous comparison, maintaining uniformity across embedding layers, normalization techniques, and Dropout strategies. Results indicate that the BiLSTM + CRF architecture outperforms its counterparts by adeptly handling the syntactic structures prevalent in bibliographic data, achieving an F1-Score of 0.96. This outcome highlights the necessity of aligning model architecture with the specific syntactic demands of bibliographic reference segmentation tasks. Consequently, the study establishes the BiLSTM + CRF model as a superior approach within the current state-of-the-art, offering a robust solution for the challenges faced in digital library management and scholarly communication.
A Benchmark Data Set for Long-Term Monitoring in the eLTER Site Gesäuse-Johnsbachtal
Authors: Lippl Florian , Maringer Alexander , Kurka Margit , Abermann Jakob , Schöner Wolfgang , Hirschmugl Manuela
Published: May 2024

This paper gives an overview over all currently available data sets for the European Long-term Ecosystem Research (eLTER) monitoring site Gesäuse-Johnsbachtal. The site is part of the LTSER platform Eisenwurzen in the Alps of the province of Styria, Austria. It contains both protected (National Park Gesäuse) and non-protected areas (Johnsbachtal). Although the main research focus of the eLTER monitoring site Gesäuse-Johnsbachtal is on inland surface running waters, forests and other wooded land, the eLTER whole system (WAILS) approach was followed in regard to the data selection, systematically screening all available data in regard to its suitability as eLTER’s Standard Observations (SOs). Thus, data from all system strata was included, incorporating Geosphere, Atmosphere, Hydrosphere, Biosphere and Sociosphere. In the WAILS approach these SOs are key data for a whole system approach towards long term ecosystem research. Altogether, 54 data sets have been collected for the eLTER monitoring site Gesäuse-Johnsbachtal and included in the Dynamical Ecological Information Management System – Site and Data Registry (DEIMS-SDR), which is the eLTER data platform. The presented work provides all these data sets through dedicated data repositories for FAIR use. This paper gives an overview on all compiled data sets and their main properties. Additionally, the available data are evaluated in a concluding gap analysis with regard to the needed observation data according to WAILS, followed by an outlook on how to fill these gaps.