bluuebunny/crossref_metadata_2025 huggingface dataset:
Risk Factors for Recurrent Laryngeal Nerve Palsy in Thyroid Surgery: A Single Center Experience of 1147 Procedures with Intermittent Intraoperative Neuromonitoring
Authors: Tabriz Navid , Muehlbeyer Selma , Weyhe Dirk , Uslar Verena
Published: July 2024

Background: Recurrent laryngeal nerve (RLN) palsy is one possible complication during thyroid surgery. Intraoperative neuromonitoring and visualization of the nerve during surgery are standard procedures to reduce the risk of RLN palsy. This study aims to investigate new factors for RLN palsy and review ones that are already known in the literature to help surgeons prepare for the procedure. Methods: A retrospective study design was used to analyze the data of 1147 patients from a certified center for thyroid surgery. All patients underwent either total thyroidectomy or hemithyroidectomy from 2016 to 2020. The acquired information was analyzed descriptively. A logistic regression was used to analyze the independent variables of interest with the binary variable RLN palsy (yes/no). For the second aim of this study, a multiple logistic regression was applied to analyze the combined significant known and new risk factors. Results: Surgery indication for Graves’ disease (OR 14.34, p < 0.001), thyroid cancer (OR 2.39, p = 0.012), and recurrent goiter (OR 5.57, p < 0.001) increased the risk for RLN palsy significantly compared to nodular goiter in hemithyroidectomy. The duration of surgery correlated positively with a higher risk for RLN palsy (OR 1.009, p = 0.005). For gender, BMI, resection weight, left or right nerve at risk, and surgeon experience, no significant differences were found. Conclusion: Operations for Graves’ disease, thyroid cancer, and recurrent goiter have the highest risk for RLN palsy and surgeons should be alerted. The longer the operation, the higher the risk of RLN palsy. The correlation between surgery method (hemithyroidectomy vs. thyroidectomy) and RLN palsy should be carefully considered due to possible bias.
Austenite Growth Behavior and Prediction Modeling of Ti Microalloyed Steel
Authors: Wang Jun , Liu Man , Wang Lifan , He Ping , Hu Haijiang , Xu Guang
Published: July 2024

Previous studies on the austenite grain growth were mostly based on a fixed temperature, and the relationship between the austenite grain and austenitizing parameters was fitted according to the results. However, there is a lack of quantitative research on the austenite grain growth during the heating process. In the present work, based on the diffusion principle of the controlled Ti microalloying element, the diffusion process of carbonitrides containing Ti during the heating process was analyzed. Combined with the precipitation model and the austenite growth model, the prediction model of austenite grain growth of Ti microalloyed steel during different heat treatment processes was established. The austenite grain size versus the temperature at four different heating rates of 0.5, 1, 10, 100 °C/s was calculated. The grain growth behavior of austenite during the heating process of Ti microalloyed steel was studied by optical microscope, scanning electron microscope and transmission electron microscope. The experimental data of the austenite grain size was in good agreement with the calculation by the proposed model, which provides a new idea for the prediction of austenite grain size in non-equilibrium state during the heating process. In addition, for Ti-containing microalloyed steels, the austenite grain size increased with the increasing heating temperature, while it changed little by further prolonging isothermal time after certain heating time, which was related to the equilibrium degree of the precipitation and the dissolution of Ti element. The austenite grain coarsening temperature of the tested Ti microalloyed steel was estimated within 1100~1200 °C.
Multi-Scale Study of a Phase Change Material on a Tropical Island for Evaluating Its Impact on Human Comfort in the Building Sector
Authors: Liu Lisa , Hammami Nadia , Bigot Dimitri , Malet-Damour Bruno , Habas Jean-Pierre
Published: July 2024

Our study explores the utilization of a phase change material (PCM) to optimize energy efficiency and thermal comfort in buildings in tropical climates. Employing a comprehensive multi-scale approach, this research encompasses both microscopic and macroscopic analyses to rigorously evaluate the PCM’s performance under various environmental conditions. It evaluates the effect of PCMs on ambient conditions in the face of temperature variations and high humidity, utilizing experimental methods at different scales (microscopic and macroscopic). Microscopic analyses reveal the composite structure of the PCM, consisting of microencapsulated paraffin within a cellulose fiber matrix. At a macroscopic scale, experiments using two real-scale test cells evaluated thermal performance and its influence on thermal comfort. Temperature and humidity data were meticulously collected over an extended period to assess the PCM’s impact on indoor regulation. We employed type T thermocouples and flux meters to monitor thermal dynamics and energy flux across the building walls. This setup facilitated a detailed comparison of temperature variations and thermal comfort metrics between the PCM-equipped test cell and a control cell. The results indicate a seasonal duality of the PCM: beneficial in winter for thermal regulation but problematic in summer due to excessive heat retention. The conclusions highlight the importance of carefully selecting and adapting PCMs for tropical climates, thus providing valuable insights for designing sustainable buildings in regions facing similar climatic challenges.
Experimental Study on Impact Performance of Basalt-Polypropylene Fiber Reinforced High-Performance Concrete
Authors: Zhang Maoyu , Li Bo , Zheng Zezhong , Zhang Jicheng
Published: July 2024

To enhance the impact resistance of high-performance concrete (HPC), a novel efficient solution was adopted by incorporating basalt fibers (BF) and polypropylene fibers (PF) as reinforcement materials in this work. To this end, the effects of single BF (BHC) and PF (PHC) as well as their combinations (BPHPC) on the impact energy consumption, ductility ratio, and toughness factor were explored through drop weight impact test of concrete considering fiber volume contents (0.1%, 0.15%, 0.2%) to evaluate the impact resistance of the concrete. The Weibull distribution function model is used to fit the drop weight impact test results and predict the probability of failure. Moreover, the fracture-resistance enhancement mechanism of fiber is analyzed at a microscopic level. Test results showed that the number of impacts resisted by the HPC can follow well the two-parameter Weibull distribution. Compared with the single BF and single PF, the combination of 0.15% BF and 0.1% PF yields favorable impact resistance, thus exhibiting a positive hybrid effect.
Optimal Limestone Content on Hydration Properties of Ordinary Portland Cement with 5% Ground Granulated Blast-Furnace Slag
Authors: Kang Ingyu , Shin Sangchul , Kim Jinman
Published: July 2024

In this study, the effect of limestone content on the mechanical performance and the heat of hydration of ordinary Portland cement (OPC) was investigated. Changes in the phase assemblage were analyzed through XRD and thermodynamic modeling. The purpose of the study was to identify the optimal limestone content in OPC. As a result of the experiment, all samples were found to have equal fluidity. Increasing the limestone content accelerated the hydration of the cement before approximately 13 h and shortened the setting time due to the acceleration of the initial hydration reaction. The compressive strength of the cement mortar showed a dilution effect, with lower compressive strength compared to the reference sample at an early age, but it gradually recovered at a later age. This is because, as shown in the XRD and thermodynamic modeling results, the carboaluminate phases formed due to the chemical effect of limestone contributed to the development of compressive strength. As a result, within the scope of this study, it is believed that maintaining the limestone content in OPC within 10% is optimal to minimize quality degradation.
Redox Stability Optimization in Anode-Supported Solid Oxide Fuel Cells
Authors: Wang Yu , Song Ming
Published: July 2024

For Ni-YSZ anode-supported solid oxide fuel cells (SOFCs), the main drawback is that they are susceptible to reducing and oxidizing atmosphere changes because of the Ni/NiO volume variation. The anode expansion upon oxidation can cause significant stresses in the cell, eventually leading to failure. In order to improve the redox stability, an analytical model is developed to study the effect of anode structure on redox stability. Compared with the SOFC without AFL, the tensile stresses in the electrolyte and cathode of SOFC with an anode functional layer (AFL) after anode oxidation are increased by 27.07% and 20.77%, respectively. The thickness of the anode structure has a great influence on the structure’s stability. Therefore, the influence of anode thickness and AFL thickness on the stress in these two structures after oxidation is also discussed. The thickness of the anode substrate plays a more important role in the SOFC without AFL than in the SOFC with AFL. By increasing the thickness of the anode substrate, the stresses in the electrolyte and cathode decrease. This method provides a theoretical basis for the design of a reliable SOFC in the redox condition and will be more reliable with more experimental proofs in the future.
Effect of AlN on the Mechanical and Electrochemical Properties of Aluminum Metal Matrix Composites
Authors: Abdelatty Rokaya H. , Radwan Ahmed Bahgat , Youssef Khaled , Ijaz Muhammad Farzik , Abdul Shakoor Rana
Published: July 2024

In the present investigation, aluminum metal matrix composites (AMMs) reinforced with aluminum nitride (AlN) nanoparticulates at different volumetric ratios of (0, 0.5, 1, 1.5, and 2 vol.%) were manufactured via a microwave-assisted powder metallurgy technique. The morphological, physical, mechanical, and electrochemical properties of the produced billets were examined to reflect the impact of the successive addition of AlN into the aluminum (Al) matrix. The morphological analysis revealed the high crystalline patterns of the formation of the Al-AlN composites. The microstructural analysis confirmed the presence of the elemental constituents of Al and AlN particles in the fabricated composites, showing an enhanced degree of agglomeration in conjunction with the additional amount of AlN. Positive behavior exhibited by the micro- and nanohardness was noticeable in the Al-AlN composites, especially at the ultimate concentration of AlN in the Al matrix of a 2 vol.%, where it reached 669.4 ± 28.1 MPa and 659.1 ± 11 MPa compared to the pure Al metal at 441.2 ± 20 MPa and 437.5 ± 11 MPa, respectively. A declining trend in the compressive strength was recorded in the reinforced Al samples. The corrosion resistance of the AlN-reinforced Al metal matrix was estimated at 3.5 wt.% NaCl using electrochemical impedance spectroscopy and potentiodynamic polarization. The results reveal that the inclusion of 2.0 vol.%AlN led to the lowest corrosion rate.
Preparation of High-Performance Barium Titanate Composite Hydrogels by Deep Eutectic Solvent-Assisted Frontal Polymerization
Authors: Li Bin , Wu Aolin , Zhou Mengjing , Wang Ying , Hu Zhigang , Su Lihua
Published: July 2024

This study aimed to develop composite hydrogels with exceptional piezoelectric properties and pressure sensitivity. To achieve the objective, this study created a deep eutectic solvent (DES) by mixing choline chloride (ChCl), acrylamide (AM), and acrylic acid (AA). Barium titanate nanoparticles (BTNPs) were incorporated as fillers into the deep eutectic solvents (DES) to synthesize the composite hydrogels using frontal polymerization (FP). The mechanical and piezoelectric properties of the resulting composite hydrogels were analyzed using Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM). This study found that the BTNPs/P(AM-co-AA) composite hydrogels exhibited excellent mechanical and piezoelectric properties. This is attributed to the high dielectric constant of BTNPs and the electrode polarization phenomenon when subjected to pressure. With a BTNPs content of 0.6 wt%, the maximum compressive strength increased by 3.68 times compared with the hydrogel without added BTNPs. Moreover, increasing the BTNPs content to 0.6 wt% resulted in a 1.48 times increase in generated voltage under the same pressure, compared with the hydrogel with only 0.2 wt% BTNPs. This study provides a method for preparing composite hydrogels with outstanding piezoelectric properties and pressure sensitivity.
Carbon Fiber-Based Vitrimer Composites: A Path toward Current Research That Is High-Performing, Useful, and Sustainable
Authors: Kumar Vishal , Kuang Wenbin , Fifield Leonard S.
Published: July 2024

In the polymeric material industry, thermosets and related composites have played a substantial role in the production of rubber and plastics. One important subset of these is thermoset composites with carbon reinforcement. The incorporation of carbon fillers and fibers gives polymeric materials improved electrical and mechanical properties, among other benefits. However, the covalently crosslinked network of thermosets presents significant challenges for recycling and reprocessing because of its intractable nature. The introduction of vitrimer materials opens a new avenue to produce biodegradable and recyclable thermosets. Carbon-reinforced vitrimer composites are pursued for high-performance, long-lasting materials with attractive physical properties, the ability to be recycled and processed, and other features that respond uniquely to stimuli. The development of carbon-reinforced vitrimer composites over the last few years is summarized in this article. First, an overview of vitrimers and the methods used to prepare carbon fiber-reinforced vitrimer composites is provided. Because of the vitrimer nature of such composites, reprocessing, healing, and recycling are viable ways to greatly extend their service life; these approaches are thoroughly explained and summarized. The conclusion is our prediction for developing carbon-based vitrimer composites.
Uterine Mesenchymal Tumors: Updates on Pathology, Molecular Landscape, and Therapeutics
Authors: Alodaini Amal A.
Published: July 2024

Background: Mesenchymal uterine tumors are a diverse group of neoplasms with varying biological potential. Many of these neoplasms can have overlapping morphologic similarities, which, in some instances, render their diagnosis and categorization thorough histomorphologic examination inconclusive. In the last decade, an exponential amount of molecular data aiming to more accurately characterize and, consequently, treat these tumors have accumulated. Objective: The goal of this narrative review is to provide a pathologic review, a genetic update, and to know the new therapeutic avenues of primary uterine mesenchymal neoplasms.
Multi-Output Prediction Model for Basic Oxygen Furnace Steelmaking Based on the Fusion of Deep Convolution and Attention Mechanisms
Authors: Dong Qianqian , Li Min , Hu Shuaijie , Yu Yan , Gu Maoqiang
Published: July 2024

The objective of basic oxygen furnace (BOF) steelmaking is to achieve molten steel with final carbon content, temperature, and phosphorus content meeting the requirements. Accurate prediction of the above properties is crucial for end-point control in BOF steelmaking. Traditional prediction models typically use multi-variable input and single-variable output approaches, neglecting the coupling relationships between different property indicators, making it difficult to predict multiple outputs simultaneously. Consequently, a multi-output prediction model based on the fusion of deep convolution and attention mechanism networks (FDCAN) is proposed. The model inputs include scalar data, such as the properties of raw materials and target molten steel, and time series data, such as lance height, oxygen supply intensity, and bottom air supply intensity during the blowing process. The FDCAN model utilizes a fully connected module to extract nonlinear features from scalar data and a deep convolution module to process time series data, capturing high-dimensional feature representations. The attention mechanism then assigns greater weight to significant features. Finally, multiple multi-layer perceptron modules predict the outputs—final carbon content, temperature, and phosphorus content. This structure allows FDCAN to learn complex relationships within the input data and between input and output variables. The effectiveness of the FDCAN model is validated using actual BOF steelmaking data, achieving hit rates of 95.14% for final carbon content within ±0.015 wt%, 84.72% for final temperature within ±15 °C, and 88.89% for final phosphorus content within ±0.005 wt%.
Full-Field Strain and Failure Analysis of Titanium Alloy Diamond Lattice
Authors: Distefano Fabio , Rizzo Daniele , Briguglio Giovanni , Crupi Vincenzo , Epasto Gabriella
Published: July 2024

The advancement in additive manufacturing has significantly expanded the use of lattice structures in many engineering fields. Titanium diamond lattice structures, produced by a direct metal laser sintering process, were experimentally investigated. Two cell sizes were selected at five different relative densities. Morphological analysis was conducted by digital microscopy. The compressive tests and digital image correlation technique allowed the evaluation of elastic moduli to be used in the Gibson–Ashby model. Failure mechanisms of the structures have been analysed by digital image correlation, which represents a promising technique for strain evaluation of such structures. A non-linear finite element model of the lattice structures was developed and validated using the experimental data. The analysis of the results highlights the good mechanical properties of the Ti6Al4V alloy lattice structures.
Study on Grain Boundary Mechanical Behaviors of Polycrystalline γ-TiAl Using Molecular Dynamics Simulations
Authors: Zhao Wenjuan , He Maoqing , Li Chunliang , Chen Wei
Published: July 2024

In this study, the molecular dynamics (MD) method was used to study the tensile deformation of polycrystalline γ-TiAl with complex and random grain orientations. Firstly, the tensile deformation was simulated with different average grain sizes (8.60 nm, 6.18 nm, and 4.50 nm) and strain rates (1 × 108 s−1, 5 × 108 s−1, and 1 × 109 s−1). The results show that the peak stress increases with an increase in tensile strain rate, and the peak stress decreases as the grain size decreases, showing an inverse Hall–Petch effect. Upon observing atomic configuration evolution during tensile deformation, it is found that the grain boundary is seriously distorted, which indicates obvious grain boundary sliding occurring. With a further increase in the loading, some dislocations nucleate at the grain boundaries and propagate towards the interior of the grains along the grain boundaries, which demonstrates that dislocation motion is the primary coordination of the mechanical process of the grain boundaries. The dislocation density near the grain boundaries continues to increase, leading to the generation of micro-cracks and eventually causing material failure. Another interesting phenomenon is that the grains rotate, and the specific rotation angle values of each grain are quantitatively calculated. Grain rotation relaxes the stress concentration near the grain boundaries and plays a toughening role. Consequently, the plastic deformation behaviors of polycrystalline γ-TiAl are achieved through the grain boundary mechanical process, that is, grain boundary sliding and grain rotation.
Metabolomics and Multi-Omics Determination of Potential Plasma Biomarkers in PRV-1-Infected Atlantic Salmon
Authors: Ivanova Lada , Rangel-Huerta Oscar D. , Tartor Haitham , Dahle Maria K. , Uhlig Silvio , Fæste Christiane Kruse
Published: July 2024

Metabolomic analysis has been explored to search for disease biomarkers in humans for some time. The application to animal species, including fish, however, is still at the beginning. In the present study, we have used targeted and untargeted metabolomics to identify metabolites in the plasma of Atlantic salmon (Salmo salar) challenged with Piscine orthoreovirus (PRV-1), aiming to find metabolites associated with the progression of PRV-1 infection into heart and skeletal muscle inflammation (HSMI). The metabolomes of control and PRV-1-infected salmon were compared at three time points during disease development by employing different biostatistical approaches. Targeted metabolomics resulted in the determination of affected metabolites and metabolic pathways, revealing a substantial impact of PRV-1 infection on lipid homeostasis, especially on several (lyso)phosphatidylcholines, ceramides, and triglycerides. Untargeted metabolomics showed a clear separation of the treatment groups at later study time points, mainly due to effects on lipid metabolism pathways. In a subsequent multi-omics approach, we combined both metabolomics datasets with previously reported proteomics data generated from the same salmon plasma samples. Data processing with DIABLO software resulted in the identification of significant metabolites and proteins that were representative of the HSMI development in the salmon.
Editorial for Special Issue: “Geochemistry and Mineralogy of Basic–Ultrabasic and Alkaline Intrusions and Related Magmatic Deposits”
Authors: Krivolutskaya Nadezhda
Published: July 2024

Magmatic deposits are sources of strategic metals provided to the global market [...]
Stability Analysis of a Mine Wall Based on Different Roof-Contact Filling Rates
Authors: Guo Jiang , Yang Wenjun , Zhao Yan , Zhang Wanzhong
Published: July 2024

This study takes the mine wall of the isolated mine pillar in the Dongguashan Copper Mine as the research object. Based on the mechanical model of the mine wall under the trapezoidal loading of the backfill, the expressions for calculating the safety factor of the mine wall were derived by considering the load-bearing conditions of the backfill–mine-wall system under different roof-contacted filling rates. On this basis, the variation law of the safety factor of the mine wall with the roof-contacted filling rate was obtained, and the calculation result was verified by a numerical simulation and a field test. The research shows that for the same mine wall width, when the roof-contacted filling rate exceeds 9.53%, the safety factor of the mine wall exhibits a “trapezoidal” variation pattern with the increase in the roof-contacted filling rate. Moreover, the comprehensive benefits of isolated pillar recovery are made more credible by maintaining a wall width of 3 m and a filler jointing rate between 30% and 74.49%. This study analyzes the effect of the roof-contacted filling rate on the stability of the mine wall, which can provide a theoretical basis for mining isolated pillars by the filler method in deep mines.
Metallurgical Copper Recovery Prediction Using Conditional Quantile Regression Based on a Copula Model
Authors: Hernández Heber , Díaz-Viera Martín , Alberdi Elisabete , Oyarbide-Zubillaga Aitor , Goti Aitor
Published: July 2024

This article proposes a novel methodology for estimating metallurgical copper recovery, a critical feature in mining project evaluations. The complexity of modeling this nonadditive variable using geostatistical methods due to low sampling density, strong heterotopic relationships with other measurements, and nonlinearity is highlighted. As an alternative, a copula-based conditional quantile regression method is proposed, which does not rely on linearity or additivity assumptions and can fit any statistical distribution. The proposed methodology was evaluated using geochemical log data and metallurgical testing from a simulated block model of a porphyry copper deposit. A highly heterotopic sample was prepared for copper recovery, sampled at 10% with respect to other variables. A copula-based nonparametric dependence model was constructed from the sample data using a kernel smoothing method, followed by the application of a conditional quantile regression for the estimation of copper recovery with chalcocite content as secondary variable, which turned out to be the most related. The accuracy of the method was evaluated using the remaining 90% of the data not included in the model. The new methodology was compared to cokriging placed under the same conditions, using performance metrics RMSE, MAE, MAPE, and R2. The results show that the proposed methodology reproduces the spatial variability of the secondary variable without the need for a variogram model and improves all evaluation metrics compared to the geostatistical method.
p-Type Schottky Contacts for Graphene Adjustable-Barrier Phototransistors
Authors: Strobel Carsten , Chavarin Carlos Alvarado , Knaut Martin , Albert Matthias , Heinzig André , Gummadi Likhith , Wenger Christian , Mikolajick Thomas
Published: July 2024

The graphene adjustable-barriers phototransistor is an attractive novel device for potential high speed and high responsivity dual-band photodetection. In this device, graphene is embedded between the semiconductors silicon and germanium. Both n-type and p-type Schottky contacts between graphene and the semiconductors are required for this device. While n-type Schottky contacts are widely investigated, reports about p-type Schottky contacts between graphene and the two involved semiconductors are scarce. In this study, we demonstrate a p-type Schottky contact between graphene and p-germanium. A clear rectification with on–off ratios of close to 103 (±5 V) and a distinct photoresponse at telecommunication wavelengths in the infrared are achieved. Further, p-type silicon is transferred to or deposited on graphene, and we also observe rectification and photoresponse in the visible range for some of these p-type Schottky junctions. These results are an important step toward the realization of functional graphene adjustable-barrier phototransistors.
Children’s Iodine Intake from Dairy Products and Related Factors: A Cross-Sectional Study in Two Provinces of China
Authors: Zhang Ying , Wang Haiyan , Ma Wei , Li Xiuwei , Wang Jianqiang , Wang Jinpeng , Xu Jing
Published: July 2024

Dairy products are a significant source of iodine, and their contribution to iodine intake must be evaluated regularly. However, there is a lack of data on iodine intake from dairy products in China. Through a cross-sectional study, we determined the iodine content of dairy products in the Chinese diet and estimated iodine intake among Chinese children. Intake records for 30 consecutive days were used to investigate the consumption of dairy products by 2009 children from Yunnan and Liaoning Provinces. The iodine contents of 266 dairy products with high intake frequency were determined using inductively coupled plasma–mass spectrometry (ICP-MS). We then calculated the iodine intake and contribution of dairy products and explored the related factors of dairy iodine intake through a generalized linear mixed model. Ultra-high-temperature (UHT) sterilized milk accounted for 78.7% of the total dairy products, with an iodine content of 23.0 μg/100 g. The dairy product intake rate of children in China was 83.6%, with an average daily intake of 143.1 g. The median iodine intake from milk and dairy was 26.8 μg/d, 41.5% of the estimated average recommendation (EAR) for younger children and 31.8% of the EAR for older children. The daily milk iodine intake of children in Yunnan Province was 9.448 μg/day lower than that of children in Liaoning Province (p < 0.001), and the daily iodine intake of children in rural areas was 17.958 μg/day lower than that of children in urban areas (p < 0.001). Chinese dairy products were rich in iodine, and the content of iodine was intermediate to that reported in Europe and the USA. However, children’s daily intake of milk iodine was lower than that of children in other developed countries due to the lower daily intake of dairy products, especially those in rural areas.
Importance Assigned to Breastfeeding by Spanish Pregnant Women and Associated Factors: A Survey-Based Multivariate Linear Correlation Study
Authors: Arnedillo-Sánchez Socorro , Suffo-Abouza Jose , Carmona-Rodríguez Miguel , Morilla-Romero-de-la-Osa Rubén , Arnedillo-Sánchez Inmaculada
Published: July 2024

Breastfeeding education, across all disciplines, is often inconsistent and lacking in expertise and confidence. However, recommendations from health professionals, the sociocultural environment, and previous knowledge and experiences significantly influence women’s decision to breastfeed. This study aimed to identify factors that promote the assignment of greater importance to breastfeeding and associated practical benefits. This retrospective cross-sectional study included 276 participants who completed a self-administered questionnaire. Descriptive and bivariate analyses were performed, and multivariate linear models were applied to identify factors influencing the importance assigned to breastfeeding. Most participants were married or in a relationship, were native Spaniards, had secondary or higher education, and had an average age of 32.6 years. Seventy percent met the physical activity recommendations, and 91% felt comfortable with their body image during pregnancy. The importance assigned to breastfeeding was high across various aspects, except for postpartum weight loss and body image. Group prenatal care was only significantly associated with the importance assigned to the breastfeeding technique (how to breastfeed). The obesogenic environment and the importance assigned to nutritional aspects and physical activity also turned out to be predictors, although not for all models. In our region, the educational strategy of antenatal care groups could contain gaps regarding the mother’s health, which should be addressed in the future to improve results regarding the initiation and continuation of breastfeeding.
Assessment of Vitamin D Status in the Drâa-Tafilalet Population (Morocco) Based on Sociodemographic, Health, and Nutritional Factors
Authors: Sebbari Fouzia , Khallouki Farid , Salamatullah Ahmad Mohammad , Bourhia Mohammed , Metouekel Amira , El Bouhali Bachir
Published: July 2024

The purpose of this study was to evaluate the vitamin D status and determine the factors influencing it in the Drâa-Tafilalet community (southeastern Morocco). Sociodemographic factors, health, cognitive status, sun exposure, and nutritional conditions were examined to help us understand their association with vitamin D status. Vitamin D data were gathered through laboratory testing, while demographic and health information was collected through interviews with participants in 2023. The study involved 100 participants aged 60 and above, most of whom were women (85%) rather than men (15%). The majority of participants were Arabs (90%), with a minority being Amazigh (10%). The average vitamin D level was 31.83 ± 10.55 ng/mL, varying based on participants’ age, education, and gender. Sun-exposed individuals exhibited significantly higher mean vitamin D levels (33.56 ± 11.99 ng/mL) compared to those with limited sun exposure (28.97 ± 9.28 ng/mL). Moreover, the time spent outdoors, seasonal changes, and the duration of sun exposure affected the levels of vitamin D. These findings depict the vitamin D status of the elderly population of Drâa-Tafilalet, recognized as one of Morocco’s poorest regions, shedding light on the significant influencers. Nonetheless, additional research is necessary to explore the correlation between dietary habits, sunlight exposure, and vitamin D levels in both young and elderly populations.
Mass Spectrometry of Collagen-Containing Allogeneic Human Bone Tissue Material
Authors: Ryabov Nikolay A. , Volova Larisa T. , Alekseev Denis G. , Kovaleva Svetlana A. , Medvedeva Tatyana N. , Vlasov Mikhail Yu.
Published: July 2024

The current paper highlights the active development of tissue engineering in the field of the biofabrication of living tissue analogues through 3D-bioprinting technology. The implementation of the latter is impossible without important products such as bioinks and their basic components, namely, hydrogels. In this regard, tissue engineers are searching for biomaterials to produce hydrogels with specified properties both in terms of their physical, mechanical and chemical properties and in terms of local biological effects following implantation into an organism. One of such effects is the provision of the optimal conditions for physiological reparative regeneration by the structural components that form the basis of the biomaterial. Therefore, qualitative assessment of the composition of the protein component of a biomaterial is a significant task in tissue engineering and bioprinting. It is important for predicting the behaviour of printed constructs in terms of their gradual resorption followed by tissue regeneration due to the formation of a new extracellular matrix. One of the most promising natural biomaterials with significant potential in the production of hydrogels and the bioinks based on them is the polymer collagen of allogeneic origin, which plays an important role in maintaining the structural and biological integrity of the extracellular matrix, as well as in the morphogenesis and cellular metabolism of tissues, giving them the required mechanical and biochemical properties. In tissue engineering, collagen is widely used as a basic biomaterial because of its availability, biocompatibility and facile combination with other materials. This manuscript presents the main results of a mass spectrometry analysis (proteomic assay) of the lyophilized hydrogel produced from the registered Lyoplast® bioimplant (allogeneic human bone tissue), which is promising in the field of biotechnology. Proteomic assays of the investigated lyophilized hydrogel sample showed the presence of structural proteins (six major collagen fibers of types I, II, IV, IX, XXVII, XXVIII were identified), extracellular matrix proteins, and mRNA-stabilizing proteins, which participate in the regulation of transcription, as well as inducer proteins that mediate the activation of regeneration, including the level of circadian rhythm. The research results offer a new perspective and indicate the significant potential of the lyophilized hydrogels as an effective alternative to synthetic and xenogeneic materials in regenerative medicine, particularly in the field of biotechnology, acting as a matrix and cell-containing component of bioinks for 3D bioprinting.
Dynamic Recyclable High-Performance Epoxy Resins via Triazolinedione–Indole Click Reaction and Cation–π Interaction Synergistic Crosslinking
Authors: He Ming , Li Jing , Xu Jiajing , Wu Lukun , Li Ning , Zhang Shuai
Published: July 2024

Thermosetting plastics exhibit remarkable mechanical properties and high corrosion resistance, yet the permanent covalent crosslinked network renders these materials challenging for reshaping and recycling. In this study, a high-performance polymer film (EI25-TAD5-Mg) was synthesized by combining click chemistry and cation–π interactions. The internal network of the material was selectively constructed through flexible triazolinedione (TAD) and indole via a click reaction. Cation–π interactions were established between Mg2+ and electron-rich indole units, leading to network contraction and reinforcement. Dynamic non-covalent interactions improved the covalent crosslinked network, and the reversible dissociation of cation–π interactions during loading provided effective energy dissipation. Finally, the epoxy resin exhibited excellent mechanical properties (tensile strength of 91.2 MPa) and latent dynamic behavior. Additionally, the thermal reversibility of the C-N click reaction and dynamic cation–π interaction endowed the material with processability and recyclability. This strategy holds potential value in the field of modifying covalent thermosetting materials.
The Impact of Lignin Biopolymer Sources, Isolation, and Size Reduction from the Macro- to Nanoscale on the Performances of Next-Generation Sunscreen
Authors: Girard Victor , Fragnières Léane , Chapuis Hubert , Brosse Nicolas , Marchal-Heussler Laurent , Canilho Nadia , Parant Stéphane , Ziegler-Devin Isabelle
Published: July 2024

In recent years, concerns about the harmful effects of synthetic UV filters on the environment have highlighted the need for natural sun blockers. Lignin, the most abundant aromatic renewable biopolymer on Earth, is a promising candidate for next-generation sunscreen due to its inherent UV absorbance and its green, biodegradable, and biocompatible properties. Lignin’s limitations, such as its dark color and poor dispersity, can be overcome by reducing particle size to the nanoscale, enhancing UV protection and formulation. In this study, 100–200 nm lignin nanoparticles (LNPs) were prepared from various biomass by-products (hardwood, softwood, and herbaceous material) using an eco-friendly anti-solvent precipitation method. Pure lignin macroparticles (LMPs) were extracted from beech, spruce, and wheat straw using an ethanol–organosolv treatment and compared with sulfur-rich kraft lignin (KL). Sunscreen lotions made from these LMPs and LNPs at various concentrations demonstrated novel UV-shielding properties based on biomass source and particle size. The results showed that transitioning from the macro- to nanoscale increased the sun protection factor (SPF) by at least 2.5 times, with the best results improving the SPF from 7.5 to 42 for wheat straw LMPs and LNPs at 5 wt%. This study underscores lignin’s potential in developing high-quality green sunscreens, aligning with green chemistry principles.
Comparing the Dominant Factors in Coastal Morphology: Inappropriate Infrastructure vs. Climate Change—A Case Study of the Hsinchu Fishery Harbor, Taiwan
Authors: Hsu Jui-Chan , Huang Wei-Po , Ye Chun-Jhen
Published: July 2024

The construction of coastal infrastructure alters the natural hydrodynamics, leading to irreversible changes in coastal morphology. Furthermore, there has been an increasing concern about global climate change in recent years, which requires examining how climatic shifts impact the mechanisms that govern oceanic processes, the trends in morphological changes, the extent of the impacts, and the corresponding weightings assigned to coastal infrastructure. This study aims to assess the impacts of climate change on the wave distribution and coastal morphology around the two breakwaters perpendicular to the shoreline of Hsinchu Fishery Harbor in Taiwan at the end of the 21st century. The findings reveal that, by the end of the century, during extreme climatic events, such as typhoons (increasing the maximum wind speed and extreme sea levels), the wave heights around the Hsinchu Fishery Harbor, compared to the present day, may increase by 5.94% to 81.25%. Regarding the potential coastal morphological changes, erosion trends are evident around the harbor, but there is a pronounced tendency toward accretion in the sheltered area. The impact range and weightings of the Hsinchu Fishery Harbor breakwaters under climate change on coastal morphology were then determined based on historical bathymetric data and simulated bathymetric changes using the empirical orthogonal function (EOF) method. Under different-intensity climate change scenarios, the EOF analysis indicates no significant differences in the impact range and weightings on coastal morphological changes. In light of the analysis results, it is evident that structures have a much more substantial impact on coastal morphological change than climate change does.
Effects of Nitrogen Fertilizer Application on Soil Properties and Arsenic Mobilization in Paddy Soil
Authors: Han Bing , Chen Wei-Qing , Jiao Yong-Qiang , Yang Rui , Niu Li-Lu , Chen Xin-Ran , Ji Chen-Yang , Yin Dai-Xia
Published: July 2024

Anthropogenic nitrogen (N) fertilization may substantially alter arsenic (As) behavior in the soil. However, a comprehensive understanding of how the soil As cycle responds to external N addition remains elusive. This study investigates the effects of various N fertilizers on soil properties and As mobility in paddy soil. Regardless of N sources, the concentrations of soluble As and SPLP-extractable As decreased with all N applications. Similarly, soil acidification occurred and dissolved iron (Fe) increased in most treatments, except for KNO3 addition. However, only the KNO3 application could reduce As desorption from soil minerals based on phosphate extraction. Also, KNO3 enhanced both soil catalase (S-CAT) and dehydrogenase (S-DEH) activities. Other N treatments decreased S-CAT activities, but increased S-DEH activities. Principal components analysis indicated that phosphate extractable As was associated with NH4+-N concentration and S-DEH activity, while the concentrations of soluble As and SPLP-extractable As were associated with pH, S-CAT activity, and dissolved Fe. These results demonstrated that the soil properties induced by the N application are the main drivers of As desorption in paddy soil and that KNO3 application is more eco-friendly than other N sources in As-contaminated paddy soil. This study shed light on the reasonable application of N-bearing fertilizers and the importance of soil properties to assess As mobility in As-contaminated paddy soil.
Assessing the Climate Change Impacts on Maize Production in the Slovak Republic and Their Relevance to Sustainability: A Case Study
Authors: Benďáková Viktória , Nagy Henrietta , Turčeková Natália , Adamičková Izabela , Bielik Peter
Published: July 2024

Climate change poses a significant challenge to the agricultural sector, with far-reaching implications on a global scale. As the agriculture sector plays a critical role in the economy of the Slovak Republic, it is crucial to understand the impacts of climate change and, with it, the vulnerabilities that agricultural practices face. Agricultural production and food sustainability are intricately linked to various factors, including population growth and the effects of climate change. This paper focuses on analyzing the production of maize in Slovakia and identifying the factors driving its cultivation. We aim to assess how climate factors influence maize yields across different temperature and precipitation levels through comprehensive data analysis and statistical methods. By utilizing the stochastic production function proposed by Just and Pope (1979) for 1996 to 2022 and estimating model parameters using GRETL software, we aim to provide insights into the relationship between climate change and maize production. Furthermore, we explore the implications of our findings for the sustainability of agricultural practices in Slovakia. Our analysis reveals that the impact of temperature and precipitation on maize yield varies by month and exhibits a nonlinear nature, with climate changes generally exerting a negative influence. Understanding these dynamics is crucial for developing sustainable agricultural strategies that can mitigate the adverse effects of climate change on maize production and ensure long-term food security.
Dual-Wheel Drive of Government Subsidies and Technical Support: A Study on the Mechanism of Promoting Rural Residents’ Green Production
Authors: Wu Songze , Xie Jiehui , Tian Fujun , Chen Qian , Liu Yan
Published: July 2024

It is of great significance to explore the effect of government subsidies and technical support on rural residents’ green production for improving the level of agricultural green development in the context of the green and high-quality development. Based on the theory of rural residents’ behavior, this paper empirically examined the impact of government subsidies and technical support on rural residents’ green production by using the ordered logit model and household survey data of CLES2022. Additionally, it applied the mediating effects model to explore the transmission mechanism. The results indicate that: (1) Government subsidies and technical support have a significant positive influence on rural residents’ green production. After controlling the characteristics of individuals, families, and cultivated land, the path coefficient is determined to be 0.032, which is significant at the 0.01 level; technical support significantly affects rural residents’ green production, and the path coefficient is 0.390, which is statistically significant at the 0.05 level. The above results are still valid after a robustness test. (2) In terms of the mechanism, government subsidies and technical support promote rural residents’ green production through service outsourcing and productive assets. On this basis, the paper proposed some policy suggestions, such as giving full play to the guiding role of government subsidies, increasing government technical support, establishing a service outsourcing platform, as well as strengthening supervision and evaluation.
Fostering Resilient and Sustainable Rural Development through Nature-Based Tourism, Digital Technologies, and Built Heritage Preservation: The Experience of San Giovanni Lipioni, Italy
Authors: Costantino Carlo , Calleo Alberto , Benedetti Anna Chiara , Bartolomei Cristiana , Predari Giorgia
Published: July 2024

Situated in the province of Chieti, Italy, San Giovanni Lipioni is a representative case of depopulation, mirroring the challenges numerous rural areas across Europe face. In this regard, the present paper describes the activities of a four-year research project in collaboration with a territorial promotion association and a local action group (LAG) aimed at fostering the sustainable development of the territory, focusing on nature-based tourism, digital-based communication and activation strategies, and the preservation of built heritage. A multidisciplinary approach is employed, delving into three distinct levels, as follows: (i) a comprehensive analysis of the built heritage and the tangible and intangible culture; (ii) the activation of the nature hiking trails between surrounding municipalities; and (iii) an exploration of digital communication strategies for tourism promotion and territorial reactivation.
Powering the Future: An Integrated Framework for Clean Renewable Energy Transition
Authors: Wehbi Hanan
Published: July 2024

The transition to renewable energy has been recognized as a crucial step in addressing climate change and achieving greenhouse gas reduction targets, but it can also cause energy sprawl if not planned properly. Clean renewable energy communities (CREC) are emerging globally as an approach for decentralized energy systems and an alternative to traditional centralized energy systems. CREC aim to lower the energy carbon footprint, enhance local energy resilience, and improve the quality of life of residents. Through a comprehensive literature review, this study reviews metrics that can assess the impact of energy transition plans and support decision-making to select technologies that create efficient, reliable, and accessible energy systems. It classifies these metrics into a five-dimensional sustainability approach including environmental, technical, social, economic, and political and institutional dimensions. The paper proposes a conceptual framework to guide decision-makers in recognizing the role of sustainable land development, sustainable energy planning, and resiliency as an integrated approach to energy transition planning. This framework stresses mapping the place-based potential for clean renewable energy at various scales, highlights the importance of resilience in energy planning, and addresses challenges associated with energy source selection, built environment efficiency, and the energy trade. While the framework can serve as a starting point for evaluating energy transition plans, further work is needed to address the limitations of existing metrics and identify additional evaluations for mixed-energy land use that are critical to managing energy sprawl in terms of ecosystem services and other land uses.