bluuebunny/crossref_metadata_2025 huggingface dataset:
Long-Term Survival in BRCA1 Mutant Advanced Ovarian Cancer: Unveiling the Impact of Olaparib
Authors: Afrăsânie Vlad-Adrian , Rusu Alexandra , Gheorghe Adelina Silvana , Froicu Eliza Maria , Dumitrescu Elena Adriana , Gafton Bogdan , Alexa-Stratulat Teodora , Miron Lucian , Stănculeanu Dana Lucia , Marinca Mihai Vasile
Published: August 2024

Ovarian cancer is one of the most frequent malignancies in women. The treatment landscape underwent significant changes as new agents were introduced in ovarian cancer management over the last decade. We present two cases of long responses to Olaparib in BRCA (BReast CAncer gene) mutant ovarian cancer patients. The first case belongs to a 42-year-old female diagnosed with advanced ovarian carcinoma with a rare germinal mutation (BRCA1 c.68_69delAG, commonly found in descendants of Ashkenazi Jewish populations, but also Arabic and Asian ones) and a significant family history of ovarian and breast cancers. After poorly tolerated neoadjuvant chemotherapy, the patient underwent total hysterectomy, bilateral adnexectomy, and intraperitoneal hyperthermic chemotherapy. After eight months, the disease progressed, and first-line platinum chemotherapy was administered. Although not well-tolerated (grade 3 anemia, allergic reactions), chemotherapy resulted in a partial response, and given the patient’s characteristics, maintenance with Olaparib was recommended. Treatment is ongoing (total current duration 69 months) and tolerated well (grade 1 side effects). This case illustrates the long-term benefits that novel therapies like Olaparib may offer in patients with platinum-sensitive relapsed ovarian cancer harboring a rare BRCA mutation. The second case highlights a 55-year-old postmenopausal woman diagnosed with ovarian cancer, FIGO stage IVA. Initial treatment included six cycles of chemotherapy, which led to a partial response, followed by interval debulking surgery and another four cycles of chemotherapy. Subsequent Olaparib maintenance therapy post BRCA1 mutation identification contributed to a significant progression-free survival of 65 months until disease recurrence and secondary cytoreductive surgery, showcasing the effectiveness of PARP inhibitors in personalized oncology treatment of ovarian cancer.
Intraoperative Prediction of Coronary Graft Failure Based on Transit Time Flow Measurement: A PRELIMINARY STUDY
Authors: Kozlov Boris N. , Zatolokin Vasily V. , Mochula Andrew V. , Alisherov Yusufjon , Panfilov Dmitri S. , Kamenshchikov Nikolay O. , Kim Elena B.
Published: August 2024

Myocardial revascularization has been known to not affect the prognosis in some patients. Coronary artery bypass graft (CABG) failure may develop one year after CABG surgery. This is accompanied by a high risk of developing myocardial infarction after complete myocardial revascularization in obstructive coronary artery disease (CAD) due to microvascular dysfunction. The study of microvascular dysfunction using intraoperative stress tests with adenosine triphosphate (ATP) allows for the assessment of the coronary bypass flow reserve (CBFR) and the risk of graft failure one year after surgery. The study included 79 CAD patients (238 grafts) who underwent dynamic single-photon emission computed tomography (SPECT) before CABG and dynamic transit time flow measurement (TTFM) during CABG at rest and at stress. The CBFR was calculated by the ratio of the mean graft flow (MGF) at stress to the MGF at rest. A multivariate regression model showed that the MGF at rest (p = 0.043), the MGF at stress (p = 0.026) and the CBFR (p = 0.0001) were significant independent predictors of graft failure. As a result of ROC analysis, the threshold CBFR < 1.67 units correlated with graft failure more closely (sensitivity 82%, specificity 90%) The CBFR is a significant independent predictor of graft failure for up to 16 months.
Incidental Findings Following Dental Implant Procedures in the Mandible: A New Post-Processing CBCT Software Analysis
Authors: Garrote Marcel da Silva , Alencar Ana Helena Gonçalves de , Estrela Cyntia Rodrigues de Araújo , Estrela Lucas Rodrigues de Araújo , Bueno Mike Reis , Guedes Orlando Aguirre , Estrela Carlos
Published: August 2024

Background/Objectives: The aim of this study was to evaluate incidental findings in the mandible after the placement of dental implants using a new cone–beam computed tomography (CBCT) software. Methods: The initial sample consisted of 2872 CBCT scans of patients of both sexes. The parameters evaluated in this study were the location of the implants in the mandible, implant length, anatomical relationship of the implant with the mandibular canal, presence or absence of damage to the adjacent teeth, presence or absence of implant fractures, and presence or absence of bone support. Fisher’s exact test was performed to compare the variables. The significance level was set at p = 0.05. Results: Out of 2872 CBCT scans, 214 images of patients with an average age of 44.5 years were included. The most frequent location of the implants was the posterior region (93.5%), with 54% of the implants having a length between 9 and 14 mm. It was found that 92% of the implants were positioned above the mandibular canal. Damage to adjacent teeth was observed, with no correlation with the implant positioning (p = 1.000). In 100% of cases of implants in the anterior region, there was bone support. Fracture was observed in 1.7% of implants with a length between 9 and 14 mm. Conclusions: The installation of implants in the mandible occurs more frequently in the posterior region, with a high presence of bone support and a low incidence of damage to adjacent teeth, anatomical structures, and fractures.
Occlusal Plane, Mandibular Position and Dentoalveolar Changes during the Orthodontic Treatment with the Use of Mini-Screws
Authors: Gómez-Bedoya Julián David , Escobar-Serna Pablo Arley , Tanaka-Lozano Eliana Midori , Agudelo-Suárez Andrés A. , Ramírez-Ossa Diana Milena
Published: August 2024

This study aimed to describe the changes produced on the occlusal plane (OP), the mandibular position and the dentoalveolar compensations of patients with distalization of the maxillary/mandibular arch assisted by mini-screws (MS). A descriptive case–series study was performed using the digital lateral cephalograms (DLC) of nine patients who underwent orthodontic treatment and required the use of MS for a complete distalization of the maxillary/mandibular arch. Records were collected at three different times (T1–T2–T3) and digitally analyzed (variables: Skeletal diagnosis; maxillary occlusal plane; position of the maxilla/mandible; and dentoalveolar changes of the distalization arch tracing the longitudinal axis of incisors/molars regarding the palatal/mandibular plane). Findings show that the OP varied from T1–T2–T3 in all cases, indicating its stepping or flattening. ODI, APDI, SNA, SNB, and ANB changed minimally in all cases, without variations in the mandibular position or in the skeletal diagnosis. Dentoalveolar measurements also showed differences between T1–T2–T3. In summary, conventional orthodontic treatment modified the OP during the first phase of treatment. Moreover, the distalization mechanics with MS changed the OP and produced dentoalveolar changes, mainly in the inclination of incisors and molars. Other measures considered in the study did not change substantially.
Role of Vaccination Strategies to Host-Pathogen Dynamics in Social Interactions
Authors: Gonzaga Marlon Nunes , de Oliveira Marcelo Martins , Atman Allbens Picardi Faria
Published: August 2024

This study presents extended Immunity Agent-Based Model (IABM) simulations to evaluate vaccination strategies in controlling the spread of infectious diseases. The application of IABM in the analysis of vaccination configurations is innovative, as a vaccinated individual can be infected depending on how their immune system acts against the invading pathogen, without a pre-established infection rate. Analysis at the microscopic level demonstrates the impact of vaccination on individual immune responses and infection outcomes, providing a more realistic representation of how the humoral response caused by vaccination affects the individual’s immune defense. At the macroscopic level, the effects of different population-wide vaccination strategies are explored, including random vaccination, targeted vaccination of specific demographic groups, and spatially focused vaccination. The results indicate that increased vaccination rates are correlated with decreased infection and mortality rates, highlighting the importance of achieving herd immunity. Furthermore, strategies focused on vulnerable populations or densely populated regions prove to be more effective in reducing disease transmission compared to randomly distributed vaccination. The results presented in this work show that vaccination strategies focused on highly crowded regions are more efficient in controlling epidemics and outbreaks. Results suggest that applying vaccination only in the densest region resulted in the suppression of infection in that region, with less intense viral spread in areas with lower population densities. Strategies focused on specific regions, in addition to being more efficient in reducing the number of infected and dead people, reduce costs related to transportation, storage, and distribution of doses compared to the random vaccination strategy. Considering that, despite scientific efforts to consolidate the use of mass vaccination, the accessibility, affordability, and acceptability of vaccines are problems that persist, investing in the study of strategies that mitigate such issues is crucial in the development and application of government policies that make immunization systems more efficient and robust.
Transforming Education Leadership through Multiple Approaches to Develop and Support School Leadership
Authors: Huber Stephan Gerhard , Pruitt Jane
Published: August 2024

This article elaborates on the multiple approaches to develop and support school leadership. In a 5-year quasi-experimental longitudinal mixed-methods study based on a sample of 122 schools in three regions in a German state, 75 school leaders and their teams participated in a 3-year program using multiple approaches; the rest served as the control group. The multiple approaches covered the school leaders’ (a) professional development, comprising (i) a professional development program, (ii) individual coaching series, and (b) support for them, including (iii) school consultancy and (iv) additional financial resources. The quality of the interventions (regarding both the process and didactic qualities, as well as outcome qualities) and how the quality of both the school leadership and the schools changes over time as a consequence of these interventions are analyzed. The study’s results show a highly positive assessment of the quality and advantages of the multiple approaches and their benefits for the quality of school leadership and further aspects of the school. The regression analyses demonstrate that positively perceived outcome qualities of the interventions are associated with improvements in numerous dimensions of school quality.
OFPP-GAN: One-Shot Federated Personalized Protection–Generative Adversarial Network
Authors: Jiang Zhenyu , Zhou Changli , Tian Hui , Chen Zikang
Published: August 2024

Differential privacy techniques have shown excellent performance in protecting sensitive information during GAN model training. However, with the increasing attention to data privacy issues, ensuring high-quality output of generative models and the efficiency of federated learning while protecting privacy has become a pressing challenge. To address these issues, this paper proposes a One-shot Federated Personalized Protection–Generative Adversarial Network (OFPP-GAN). Firstly, this scheme employs dual personalized differential privacy to achieve privacy protection. It adjusts the noise scale and clipping threshold based on the gradient changes during model training in a personalized manner, thereby enhancing the performance of the generative model while protecting privacy. Additionally, the scheme adopts the one-shot federated learning paradigm, where each client uploads their local model containing private information only once throughout the training process. This approach not only reduces the risk of privacy leakage but also decreases the communication overhead of the entire system. Finally, we validate the effectiveness of the proposed method through theoretical analysis and experiments. Compared with existing methods, the generative model trained with OFPP-GAN demonstrates superior security, efficiency, and robustness.
Cross-Domain Document Summarization Model via Two-Stage Curriculum Learning
Authors: Lee Seungsoo , Kim Gyunyeop , Kang Sangwoo
Published: August 2024

Generative document summarization is a natural language processing technique that generates short summary sentences while preserving the content of long texts. Various fine-tuned pre-trained document summarization models have been proposed using a specific single text-summarization dataset. However, each text-summarization dataset usually specializes in a particular downstream task. Therefore, it is difficult to treat all cases involving multiple domains using a single dataset. Accordingly, when a generative document summarization model is fine-tuned to a specific dataset, it performs well, whereas the performance is degraded by up to 45% for datasets that are not used during learning. In short, summarization models perform well with in-domain cases, as the dataset domain during training and evaluation is the same but perform poorly with out-domain inputs. In this paper, we propose a new curriculum-learning method using mixed datasets while training a generative summarization model to be more robust on out-domain datasets. Our method performed better than XSum with 10%, 20%, and 10% lower performance degradation in CNN/DM, which comprised one of two test datasets used, compared to baseline model performance.
A Fault Diagnosis Method for Electric Check Valve Based on ResNet-ELM with Adaptive Focal Loss
Authors: Xiang Weijia , Wu Yunru , Peng Cheng , Cai Kaicheng , Ren Hongbing , Peng Yuming
Published: August 2024

Under the trend of carbon neutrality, the adoption of electric mineral transportation equipment is steadily increasing. Accurate monitoring of the operational status of electric check valves in diaphragm pumps is crucial for ensuring transportation safety. However, accurately identifying the operational characteristics of electric check valves under complex excitation and noisy environments remains challenging. This paper proposes a monitoring method for the status of electric check valves based on the integration of Adaptive Focal Loss (AFL) with residual networks and Extreme Learning Machines (AFL-ResNet-ELMs). Firstly, to address the issue of unclear feature representation in one-dimensional vibration signals, grayscale operations are employed to transform the one-dimensional data into grayscale images with more distinct features. Residual networks are then utilized to extract the state features of the check valve, with Extreme Learning Machines serving as the feature classifier. Secondly, to overcome the issue of imbalanced industrial data distribution, a new Adaptive Focal Loss function is designed. This function focuses the training process on difficult-to-classify data samples, balancing the recognition difficulty across different samples. Finally, experimental studies are conducted using industrially measured vibration data of the electric check valve. The results indicate that the proposed method achieves an average accuracy of 99.60% in identifying four health states of the check valve. This method provides a novel approach for the safety monitoring of slurry pipeline transportation processes.
Dynamic Current-Limitation Strategy of Grid-Forming Inverters Based on SR Latches
Authors: Zhang Huajie , Ma Junpeng , Li Xiaopeng
Published: August 2024

A grid-forming (GFM) inverter can effectively support active power and reactive power, and the stability problem induced by the low inertia can be thereby alleviated in a power electronics-dominated power system. Yet, the voltage source characteristic presented by the grid-forming inverter induces an overcurrent problem during a short-circuit fault. Furthermore, the time delay induces an inrush current in traditional digital control, triggered by a predefined timing sequence. To address the overcurrent problem of the GFM inverter controlled by the digital controller, the operation characteristics of GFM inverters under grid-voltage drops are investigated, and a mathematical model of the instantaneous fault current is established, which depicts the relationship between the instantaneous fault current’s magnitude, grid-voltage drop severity, equivalent output impedance, and current inner-loop response speed. Then, a Set–Reset (SR) latch-based dynamic current limitation with event-triggered control is proposed for the low-voltage ride-through of the GFM inverter. In the proposed method, the current limitation is enabled during grid fault, and the active and reactive powers can be recovered rapidly after fault clearance. Meanwhile, the active and reactive power references are designed to enhance synchronization stability during the grid fault. The proposed method addresses the issue of the repeated switching of virtual impedance during grid fault and achieves rapid power recovery after fault clearance. In addition, the proposed method uses the logic of event triggers to respond to the overcurrent event in real time and realize overcurrent protection. The simulation and experimental results demonstrate the effectiveness of the proposed method in current limitation and active-power recovery after fault clearance.
Optimal Scheduling of the Active Distribution Network with Microgrids Considering Multi-Timescale Source-Load Forecasting
Authors: Lu Jiangang , Du Hongwei , Zhao Ruifeng , Li Haobin , Tan Yonggui , Guo Wenxin
Published: August 2024

Integrating distributed generations (DGs) into distribution networks poses a challenge for active distribution networks (ADNs) when managing distributed resources for optimal scheduling. To address this issue, this paper proposes a day-ahead and intra-day scheduling approach based on a multi-microgrid system. It starts with a CNN-LSTM-based generation and load forecasting model to address the impact of generation and load uncertainties on the power grid scheduling. Then, an optimal day-ahead and intra-day scheduling framework for ADN and microgrids is introduced using predicted generation and load information. The day-ahead scheduling is responsible for optimizing the power interactions between ADN and the connected microgrids, while intra-day scheduling focuses on minimizing the operational costs of microgrids. The effectiveness of the proposed scheduling strategy is verified via case studies performed on a modified IEEE 33-node ADN. The results show that the network loss of ADN and the operation costs of microgrids are reduced by 17.31% and 32.81% after the microgrid is integrated into the ADN. The peak-valley difference in microgrids decreased by 13.12%. The simulation shows a significant reduction in operational costs and load fluctuations after implementing the proposed day-ahead and intra-day scheduling strategy. The seamless coordination between the day-ahead scheduling and intra-day scheduling allows for the precise adjustment of transfer power, alleviating peak load demand and minimizing network losses in the ADN system.
Enhanced Control Technique for Induction Motor Drives in Electric Vehicles: A Fractional-Order Sliding Mode Approach with DTC-SVM
Authors: Ben Salem Fatma , Almousa Motab Turki , Derbel Nabil
Published: August 2024

The present paper proposes the use of fractional derivatives in the definition of sliding function, giving a new mode control applied to induction motor drives in electric vehicle (EV) applications. The proposed Fractional-Order Sliding Mode Direct Torque Control-Space Vector Modulation (FOSM-DTC-SVM) strategy aims to address the limitations of conventional control techniques and mitigate torque and flux ripples in induction motor systems. The paper first introduces the motivation for using fractional-order control methods to handle the nonlinear and fractional characteristics inherent in induction motor systems. The core describes the proposed FOSM-DTC-SVM control strategy, which leverages a fractional sliding function and the associated Lyapunov stability analysis. The efficiency of the proposed strategy is validated via three scenarios. (i) The first scenario, where the acceleration of the desired speed is defined by pulses, leading to Dirac impulses in its second derivative, demonstrates the advantage of the proposed control approach in tracking the desired speed while minimizing flux ripples and generating pulses in the rotor pulsation. (ii) The second scenario demonstrates the effectiveness of filtering the desired speed to eliminate Dirac impulses, resulting in smoother rotor pulsation variations and a slightly slower speed response while maintaining similar flux ripples and stator current characteristics. (iii) The third scenario consists of eliminating the fractional derivatives of the pulses existing in the expression of the control, leading to the elimination of Dirac impulses. These results demonstrate the potential of the FOSM-DTC-SVM to revolutionize the performance and efficiency of EVs. By incorporating fractional control in the control scheme for PV-powered EVs, the paper showcases a promising avenue for sustainable transportation.
Quantity and Material Composition of Foreign Bodies in Bio-Waste Collected in Towns from Single- and Multi-Family Housing and in Rural Areas
Authors: Dronia Wojciech , Połomka Jacek , Jędrczak Andrzej
Published: August 2024

There is a general consensus that bio-waste is a suitable material for valorization by means of the fermentation process with the production of biogas. The success of a bio-waste closed-loop economy will ultimately be determined by the demand for the products made from it. Poor-quality composts and fermentation products will not be allowed on the market in the long term. This means that not only final products but also bio-waste from separate collections must also meet the quality requirements. The aim of this 12-month study was a monthly analysis determining the level of contaminants in bio-waste collected from rural communities, single-family neighborhoods in urban areas, and multi-family neighborhoods in urban areas. The share of contaminants in bio-waste from rural areas and single-family urban housing averaged 8.2% and 7.2%, respectively, while multi-family urban housing had a significantly higher average of 16.6%. The primary contaminants identified were treated wood, plastics, mineral wastes, paper, and glass in rural areas and plastics, paper, treated wood, glass, and textiles in urban areas. The close positive correlation found between the total content of pollutants and, in particular, with plastics and kitchen waste in bio-waste collected in rural communities and from multi-family housing in cities indicates that they are likely the main source of the origin of these pollutants.
Study of Efficient and Clean Combustion of Diesel–Natural Gas Engine at Low Loads with Concentration and Temperature Stratified Combustion
Authors: Zhang Min , Su Wanhua , Jia Zhi
Published: August 2024

The approach for achieving efficient and clean combustion in a diesel–natural gas (NG) heavy-duty engine at low loads was studied by computational fluid dynamics simulation. This study proposed the concentration and temperature-stratified combustion technology and clarified its mechanism. The results revealed that different stratified combustions can be organized by controlling the pressures, timings, and durations of diesel and NG injections, and stratified combustion can be classified into moderate, lean, and rich stratified combustion modes. Efficient and clean combustion can be realized simultaneously at low engine loads: the gross indicated thermal efficiency (ITEg) of engine breakthrough was improved to 47.9%, and the indicated-specific emissions of unburned hydrocarbon (ISUHC) were greatly reduced to 1.6 g/kWh, while the indicated-specific emissions of nitrogen oxide (ISNOx) remained at 0.6 g/kWh. Moreover, the detailed analysis of three typical stratified combustion modes demonstrates that coupling control of the concentration and temperature of the charge is the key to obtaining excellent engine performance. Most of the NG-stratified mixture should burn in the react ratio range of 0.4 to 0.8 for low unburned hydrocarbon emissions, low nitrogen oxides emissions, and rapid combustion. The proper temperature stratification should ensure that a high-temperature charge is around the over-lean NG mixture. This study can provide the fundamentals of stratified combustion control and feasible solutions for commercial applications of NG engines.
Enhanced Carbon Storage in Mixed Coniferous and Broadleaf Forest Compared to Pure Forest in the North Subtropical–Warm Temperate Transition Zone of China
Authors: Xu Wenbin , Zhang Beibei , Xu Qing , Gao Deqiang , Zuo Haijun , Ren Ranran , Diao Ke , Chen Zhicheng
Published: August 2024

Enunciating the carbon storage across various types of forests is a precondition for comprehending forest ecosystem carbon cycling. However, previous studies regarding forest carbon storage were primarily conducted in the general temperature zones, with a limited understanding of carbon storage in different forest types within climate transition zones. In this study, we employed biomass models to explore the carbon storage in three types of natural secondary forests (Pinus armandii forest, Quercus aliena forest, and Q. aliena–P. armandii mixed forest) in the transition zone between the northern subtropical and warm temperate regions of China. Furthermore, we used the variance decomposition analysis and random forest model to determine the key factors influencing carbon storage in three types of natural secondary forests. Our results indicated that the carbon storage of wood and soil layers in the Q. aliena–P. armandii mixed forest was significantly higher than that in the P. armandii and Q. aliena forests. Total carbon storage was ranked as follows: Q. aliena–P. armandii mixed forest (266.09 t/ha) > P. armandii forest (222.89 t/ha) > Q. aliena forest (212.46 t/ha). Our results also revealed that carbon storage of the wood layer was jointly regulated by environmental factors, plant physiological characteristics, and soil properties, while soil carbon storage was mainly affected by soil properties. These results highlight the significant advantages of mixed conifer–broadleaf forests in carbon storage, emphasizing the importance of mixed natural secondary forests in carbon cycling and ecosystem services. This study provides scientific evidence for enhancing forest carbon sink functions and developing forest conservation and management policies to combat climate change.
A Survey on Data Availability in Layer 2 Blockchain Rollups: Open Challenges and Future Improvements
Authors: Saif Muhammad Bin , Migliorini Sara , Spoto Fausto
Published: August 2024

Layer 2 solutions have emerged in recent years as a valuable alternative to increase the throughput and scalability of blockchain-based architectures. The three primary types of Layer 2 solutions are state channels, sidechains, and rollups. The rollups are particularly promising, allowing significant improvements in transaction throughput, security, and efficiency, and have been adopted by many real-world projects, such as Polygon and Optimistic. However, the adoption of Layer 2 solutions has led to other challenges, such as the data availability problem, where transaction data processed off-chain must be posted back on the main chain. This is crucial to prevent data withholding attacks and ensure all participants can independently verify the blockchain state. This paper provides a comprehensive survey of existing rollup-based Layer 2 solutions with a focus on the data availability problem and discusses the major advantages and disadvantages of them. Finally, an analysis of open challenges and future research directions is provided.
The Effect of Mulberry Silage Supplementation on the Carcass Fatness and Long-Chain Fatty Acid Composition of Growing Lambs Compared with Traditional Corn Silage
Authors: Cao Yang , Zhao Xiaoou , Zheng Kaizhi , Wu Jianliang , Lv Zhiqiang , Huang Xin , Jiang Yongqing , Fang Wenwen , Cao Yang , Jiang Junfang
Published: August 2024

Lamb meat has become very popular with consumers in recent years due to its nutritional benefits. As a lean red meat, lamb is an important natural source of polyunsaturated and saturated fatty acids, which can be modified by adjustments in livestock feed. This study used proteomic and metabolic analyses to compare a basal ration supplemented with either mulberry silage or corn silage. Supplementation with mulberry silage led to a reduction in subcutaneous carcass fatness compared with corn silage. Additionally, changes in the proteome associated with fatty acid metabolism and oxidation resulted in decreased levels of saturated and trans fatty acids, while significantly increasing the levels of α-linolenic acid (ALA) and oleic acid and reducing linoleic acid content.
The Preparation of W/O/W High-Internal-Phase Emulsions as Coagulants for Tofu: The Effect of the Addition of Soy Protein Isolate in the Internal Water Phase
Authors: Wang Yongquan , Liu Xuanbo , Zhang Qiang
Published: August 2024

Tofu quality is determined by a controlled coagulation process using a W/O/W emulsion coagulant. The impact of adding soy protein isolate (SPI) to the inner water phase on the stability of W/O/W high-internal-phase emulsions (HIPEs) and its application as a coagulant for tofu was assessed. No creaming occurred during 7-day storage with SPI concentrations up to 0.3%, while the emulsion droplets aggregated with 0.5% and 0.7% SPI. Emulsions containing 0.3% SPI maintained a constant mean droplet size after 21 days of storage and exhibited the lowest TURBISCAN stability index value. HIPE stability against freeze–thaw cycles improved after heating. HIPEs with SPI concentrations above 0.3% demonstrated an elastic gel-like behavior. The increased viscosity and aggregation of the protein around droplets indicated that the interaction among emulsion droplets could enhance stability. W/O/W HIPE coagulants significantly increased tofu yield, reduced hardness, and produced a more homogenous tofu gel compared to a MgCl2 solution. The HIPE with 0.3% SPI was found to be optimal for use as a coagulant for tofu.
Golden Flower Tibetan Tea Polysaccharides Alleviate Constipation in Mice by Regulating Aquaporins-Mediated Water Transport System and Gut Microbiota
Authors: Yu Manyou , Zhao Jiayuan , Xie Qingling , Deng Junlin , Zhu Yongqing , Chen Jian , Xiang Zhuoya , Zhang Ting , Liu Gang , Xia Chen , Shi Liugang , Wu Bin , Gouvinhas Irene , Barros Ana Novo
Published: August 2024

Constipation, a widespread gastrointestinal disorder, often leads to the exploration of natural remedies. This study examines the efficacy of Golden Flower Tibetan Tea Polysaccharides (GFTTPs) in alleviating constipation in mice. Chemical analyses reveal that GFTTPs possess O-H, carboxyl, carboxylic acid (-COOH), and C-O-C groups, alongside a porous crystal structure with thermal stability. In animal experiments, GFTTPs significantly upregulated aquaporin 3 (AQP3) and aquaporin 8 (AQP8) expressions in the colon, enhancing water absorption and reducing fecal water content. At a 400 mg/kg dosage, GFTTPs notably improved colonic tissue alterations and serum levels of excitatory neurotransmitters caused by loperamide hydrochloride. They also beneficially altered gut microbiota, increasing Coprococcus, Lactobacillus, and Pediococcus populations. These changes correlated with improved stool frequency, consistency, and weight in constipated mice. Importantly, GFTTPs at 200 and 400 mg/kg doses exhibited comparable effects to the normal control group in key parameters, such as gastrointestinal transit rate and fecal moisture. These findings suggest that GFTTPs may serve as a potent natural remedy for constipation, offering significant therapeutic potential within the context of gut health and with promising implications for human applications.
Identifying Key Markers for Monofloral (Eucalyptus, Rosemary, and Orange Blossom) and Multifloral Honey Differentiation in the Spanish Market by UHPLC-Q-Orbitrap-High-Resolution Mass Spectrometry Fingerprinting and Chemometrics
Authors: Rivera-Pérez Araceli , Navarro-Herrera Alba María , Garrido Frenich Antonia
Published: August 2024

Honey differentiation based on the botanical origin is crucial to guarantee product authenticity, especially considering the increasing number of fraud cases. This study assessed the metabolomic differences arising from various botanical origins in honey products sold in Spanish markets, focusing on two goals: (1) discrimination within monofloral samples (eucalyptus, rosemary, and orange blossom honey) and (2) differentiation between multifloral vs. monofloral honey samples. An omics strategy based on ultra-high-performance liquid chromatography coupled with quadrupole-Orbitrap-high-resolution mass spectrometry (UHPLC-Q-Orbitrap-HRMS) was applied for the reliable identification of specific honey markers selected by orthogonal partial least squares discriminant analysis (OPLS-DA) (R2Y = 0.929–0.981 and Q2 = 0.868–0.952), followed by the variable importance in projection (VIP) approach. Key amino acid, alkaloid, and trisaccharide markers were identified to distinguish between honey samples. Some Amadori compounds were highlighted as eucalyptus honey markers, suggesting their potential use for honey aging and botanical origin differentiation. L-phenylalanine and raffinose were markers of rosemary honey. Four markers (e.g., trigonelline, L-isoleucine, and N-(1-deoxy-1-fructosyl)isoleucine) were found in higher levels in multifloral samples, indicating a greater availability of amino acids, potentially increasing the Maillard reaction. This research is the first to address the botanical origin’s impact on honey by identifying novel markers not previously described.
Dickens Lost: A Study on the Spatial Practice in Paul Beatty’s The Sellout
Authors: Wang Ling , Xu Shuangru
Published: August 2024

Paul Beatty, as a representative writer of contemporary African American literature, pays close attention to the living space of African Americans, and their inheritance of their own history and culture in his Booker-Prize-winning novel The Sellout. Based on Henri Lefebvre’s spatial triad, this article analyzes how characters draw inspiration from their historical and cultural legacy, compete for their living space, remedy spatial injustice, and obtain their right of habitation in an erased black ghetto of Los Angeles, i.e., Dickens, with an attempt to elucidate the essence of their spatial practices of reinstituting slavery and segregation. It argues that beneath the surface of spatial change lies the pain caused by colonialism, the constraints of existing policies and the struggle of African Americans. Dickens, a seemingly marginal space, is, in effect, a representation of the negligible existence of Black people in America as well as a basis of their identity. By delving deep into the characters’ peculiar spatial practices that deconstruct state-level structural racism, this article demonstrates that Beatty criticizes the history of racial discrimination against Black people, expresses his concerns on the possible vulnerability of contemporary African Americans, and provides a new insight into their survival strategy in the so-called post-racial era.
Estimation of the Global Disease Burden of Depression and Anxiety between 1990 and 2044: An Analysis of the Global Burden of Disease Study 2019
Authors: Liu Jinnan , Ning Wei , Zhang Ning , Zhu Bin , Mao Ying
Published: August 2024

(1) Background: Depression and anxiety are the most common and severe mental disorders. This research estimated the prevalence and disease burden of depression and anxiety from 1990 to 2044. (2) Methods: Data on disease burden, population, and risk factors were identified and gathered from the Global Health Data Exchange database. The time trends, sex and age differences, key factors, and regional variations in and predictions of depression and anxiety were analyzed based on the age-standardized incidence rate, prevalence rate, and DALY rate. (3) Results: Our findings revealed that the burden of depression and anxiety was heavy. Specifically, the age-standardized DALY rate of depression started to decrease compared with trends related to anxiety disorders. Meanwhile, females bear a heavier burden for both depression and anxiety. Seniors and the middle-aged population carry the highest burden regarding mental disorders. Both high- and low-socio-demographic-index countries were found to be high-risk regions for depressive disorders. The disease burden attributed to childhood sexual abuse, bullying victimization, and intimate partner violence has increased since 1990. Finally, projections regarding depression and anxiety revealed geographic and age variations. (4) Conclusions: Public health researchers, officers, and organizations should take effective age-, sex-, and location-oriented measures.
Emotional and Work-Related Factors in the Self-Assessment of Work Ability among Italian Healthcare Workers
Authors: Magnavita Nicola , Meraglia Igor , Chiorri Carlo
Published: August 2024

The Work Ability Index (WAI) is the most commonly used tool for evaluating work capacity. Self-assessments made by workers can be influenced by various occupational and emotional factors. We wanted to study the association of work-related factors, such as work annoyance, stress, overcommitment, job satisfaction, social support, and emotional factors, such as anxiety, depression, and happiness, with work ability, in a sample of 490 healthcare workers from an Italian public health company. A principal component analysis indicated the presence of two components of the WAI questionnaire; the first expresses “subjectively estimated work ability” (SEWA), and the second refers to “ill-health-related work ability” (IHRWA). Using stepwise multiple hierarchical linear regression, we identified the factors that best predicted the total score on the WAI and on the two components. The total score was negatively predicted by anxiety, depression, a lack of happiness, low job satisfaction, overcommitment, and work annoyance. Age, being female, anxiety, and occupational stress were associated with a reduction in the IHRWA component score, while overcommitment, work annoyance, a lack of social support, depression, and a lack of happiness were negatively associated with the SEWA component. These results can help interpret those of epidemiological studies and provide guidance on ways to improve work ability.
The Reality of Healthcare Professionals in Leadership Positions at the Onset of the COVID-19 Pandemic
Authors: Shehadeh Nancy , Silva-Suarez Georgina , Ptaszek Emily , Velez Farah Roman
Published: August 2024

While pandemics have long been a topic of discussion in public health, COVID-19 placed healthcare leaders in a completely new and challenging situation. This qualitative study sought to understand the personal experiences of healthcare professionals in leadership roles at the beginning of the COVID-19 pandemic. Sixteen in-depth interviews were conducted and recorded via Zoom. Most participants were men (n = 8, 57.1%) and had a doctorate or master’s degree (n = 8, 57.1%). The themes of mental health, dynamic infrastructure, and transformative experience emerged from our participants’ narratives. Most respondents reported heightened stress during that time and shared the institutional and personal mechanisms they used to deal with the situation. They were proud of their profession and their work. They discussed the “dynamic infrastructure” they experienced at the time that helped them lead. Feeling overworked was a common experience for them. Most considered leading during COVID-19 a “transformative experience” that taught them valuable lessons. They also witnessed acts of heroism as their colleagues continued to work during difficult times, even though some succumbed to COVID-19. Despite all the challenges and uncertainties healthcare professionals in leadership positions faced at the onset of COVID-19, their resilience, dedication, and commitment to their profession prevailed. In conclusion, the firsthand experiences recounted by healthcare leaders in this study shed light on the multifaceted nature of leadership during a global health crisis. Their unwavering resilience, dedication, and commitment stand as a testament to the fortitude required in such demanding circumstances. As the COVID-19 pandemic continues to evolve, the insights gleaned from this research bear significant implications for informing future strategies and support systems aimed at bolstering healthcare leadership worldwide.
Sleep Differences in Firefighters: Barracks vs. Home
Authors: Hunnicutt Lainey E. , Corgan Makenzie , Brown Sarah R. , Nygaard Alyssa , Meares George Lesley , Collier Scott R.
Published: August 2024

It has been shown that the firefighter occupation leads to poor sleep quality and sleep architecture. Disturbed sleep in these occupations can lead to deleterious outcomes including a series of chronic diseases and illnesses such as CVD. Purpose: The aims were (1) to quantify firefighters’ sleep via polysomnography, (2) to identify differences between sleeping in the barracks versus sleeping at home, and (3) to compare firefighter data to age-matched normative data. We expected significant differences between both the home and the barrack conditions as well as significant differences when both conditions were compared to normative data. Methods: 10 male firefighters completed 3 nights of polysomnography recordings (SleepProfilerTM (Advanced Brain Monitoring, Carlsbad, CA, USA)) counterbalanced in both their own beds or barracks. A one-way rmANOVA statistical analysis was used to determine differences in sleep values with a Bonferroni correction if a significant difference was found with significance set at p < 0.05. Results: Three important variables, cortical arousals (p < 0.05), autonomic activations (p < 0.01), and spindle duration (p < 0.01), had differences that were statistically significant between sleep at home or in the barracks, with sleep in the barracks being more disturbed. Clinical differences were also observed between the home and barrack conditions and all sleep results were more deleterious when compared to normative data. Conclusions: The data demonstrates that firefighters show poor sleep quality and heavily impacted sleep architecture. This may be due to the effects of rotating shifts and occupational stress on the sleep–wake cycle. These results, when compared to age-matched normative data, show clinical manifestations of disturbed sleep in the firefighter population.
Physical and Psychological Symptomatology, Co-Parenting, and Emotion Socialization in High-Conflict Divorces: A Profile Analysis
Authors: Pellón-Elexpuru Inés , Martínez-Pampliega Ana , Cormenzana Susana
Published: August 2024

Although the consequences of divorce and conflict have been extensively studied, most research has focused on children rather than ex-spouses, although variables such as parental health or co-parenting may have an influence on children’s development through processes such as emotion socialization. In addition, the relationship between these variables has never been considered in high-conflict divorces. Therefore, the present study aimed to analyze the impact of physical and psychological symptomatology and co-parenting on the emotion socialization patterns of parents experiencing high-conflict divorces. Furthermore, the moderating role of resilience was considered, as it has been highly studied as a coping mechanism in adverse situations but barely in divorce at the parental level. For this purpose, a Latent Profile Analysis was carried out with Mplus 8.10, using a sample of 239 parents from Family Visitation Centers. Results revealed, on the one hand, that parents with fewer physical and psychological symptoms sowed more emotion socialization behaviors than those with more symptomatology. On the other hand, in situations of high interparental conflict, the role of co-parenting and resilience seems less relevant than that of physical and psychological symptomatology when analyzing parental skills like emotion socialization.
Association between Autism Spectrum Disorder and Environmental Quality in the United States
Authors: Wu Jianyong , McLain Alexander C. , Rosile Paul , Hood Darryl B.
Published: August 2024

Autism spectrum disorder (ASD) has become an emerging public health problem. The impact of multiple environmental factors on the prevalence of ASD remains unclear. This study examined the association between the prevalence of ASD and the environmental quality index (EQI), an indicator of cumulative environmental quality in five major domains, including air, water, land, built and sociodemographic variables in the United States. The results from Poisson regression models show that the prevalence of ASD has a positive association with the overall EQI with a risk ratio (RR) of 1.03 and 95% confidence intervals (CI) of 1.01–1.06, indicating that children in counties with poor environmental quality might have a higher risk of ASD. Additionally, the prevalence of ASD has a positive association with the air index (RR = 1.04, 95% CI: 1.01–1.06). These associations varied in different rural–urban groups and different climate regions. This study provided evidence for adverse effects of poor environmental quality, particularly air pollutants, on children’s neurodevelopment.
An Efficient Algorithm for Extracting Railway Tracks Based on Spatial-Channel Graph Convolutional Network and Deep Neural Residual Network
Authors: Weng Yanbin , Xu Meng , Chen Xiahu , Peng Cheng , Xiang Hui , Xie Peixin , Yin Hua
Published: August 2024

The accurate detection of railway tracks is essential for ensuring the safe operation of railways. This study introduces an innovative algorithm that utilizes a graph convolutional network (GCN) and deep neural residual network to enhance feature extraction from high-resolution aerial imagery. The traditional encoder–decoder architecture is expanded with GCN, which improves neighborhood definitions and enables long-range information exchange in a single layer. As a result, complex track features and contextual information are captured more effectively. The deep neural residual network, which incorporates depthwise separable convolution and an inverted bottleneck design, improves the representation of long-distance positional information and addresses occlusion caused by train carriages. The scSE attention mechanism reduces noise and optimizes feature representation. The algorithm was trained and tested on custom and Massachusetts datasets, demonstrating an 89.79% recall rate. This is a 3.17% improvement over the original U-Net model, indicating excellent performance in railway track segmentation. These findings suggest that the proposed algorithm not only excels in railway track segmentation but also offers significant competitive advantages in performance.