bluuebunny/crossref_metadata_2025 huggingface dataset:
Design of a 3-Bit Circularly Polarized Reconfigurable Reflectarray
Authors: Chen Zhe , Huang Chenlu , Yang Xinmi , Yan Xiaoming , Lin Xianqi , Zhou Yedi
Published: May 2024

In this paper, a 3-bit circularly polarized reconfigurable reflectarray is proposed. The array consists of 64 units in an 8 × 8 configuration, with each unit containing a circular metal patch loaded with phase-delay lines and eight PIN diodes. To independently control each unit, a corresponding DC control circuit was designed and tested with the array. In the bandwidth of 3.43–3.71 GHz, the circularly polarized reconfigurable reflectarray achieved a gain of 16 dB, an aperture efficiency of 27%, an axial ratio of ≤3 dB, an operating bandwidth of 8%, and a beam scanning range of ±60°. The circularly polarized reconfigurable reflectarray can also achieve a good dual-beam radiation performance after testing. The 3-bit circularly polarized reconfigurable reflectarray proposed in this paper offers several advantages, including low loss, high aperture efficiency, a wide beam scanning range, and excellent stability in wide-angle oblique incidence. It has potential applications in low-cost phased array, satellite communications, and deep space exploration.
A Causality-Aware Perspective on Domain Generalization via Domain Intervention
Authors: Shao Youjia , Wang Shaohui , Zhao Wencang
Published: May 2024

Most mainstream statistical models will achieve poor performance in Out-Of-Distribution (OOD) generalization. This is because these models tend to learn the spurious correlation between data and will collapse when the domain shift exists. If we want artificial intelligence (AI) to make great strides in real life, the current focus needs to be shifted to the OOD problem of deep learning models to explore the generalization ability under unknown environments. Domain generalization (DG) focusing on OOD generalization is proposed, which is able to transfer the knowledge extracted from multiple source domains to the unseen target domain. We are inspired by intuitive thinking about human intelligence relying on causality. Unlike relying on plain probability correlations, we apply a novel causal perspective to DG, which can improve the OOD generalization ability of the trained model by mining the invariant causal mechanism. Firstly, we construct the inclusive causal graph for most DG tasks through stepwise causal analysis based on the data generation process in the natural environment and introduce the reasonable Structural Causal Model (SCM). Secondly, based on counterfactual inference, causal semantic representation learning with domain intervention (CSRDN) is proposed to train a robust model. In this regard, we generate counterfactual representations for different domain interventions, which can help the model learn causal semantics and develop generalization capacity. At the same time, we seek the Pareto optimal solution in the optimization process based on the loss function to obtain a more advanced training model. Extensive experimental results of Rotated MNIST and PACS as well as VLCS datasets verify the effectiveness of the proposed CSRDN. The proposed method can integrate causal inference into domain generalization by enhancing interpretability and applicability and brings a boost to challenging OOD generalization problems.
IoT Solutions with Artificial Intelligence Technologies for Precision Agriculture: Definitions, Applications, Challenges, and Opportunities
Authors: Senoo Elisha Elikem Kofi , Anggraini Lia , Kumi Jacqueline Asor , Karolina Luna Bunga , Akansah Ebenezer , Sulyman Hafeez Ayo , Mendonça Israel , Aritsugi Masayoshi
Published: May 2024

The global agricultural sector confronts significant obstacles such as population growth, climate change, and natural disasters, which negatively impact food production and pose a threat to food security. In response to these challenges, the integration of IoT and AI technologies emerges as a promising solution, facilitating data-driven decision-making, optimizing resource allocation, and enhancing monitoring and control systems in agricultural operations to address these challenges and promote sustainable farming practices. This study examines the intersection of IoT and AI in precision agriculture (PA), aiming to provide a comprehensive understanding of their combined impact and mutually reinforcing relationship. Employing a systematic literature review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, we explore the synergies and transformative potential of integrating IoT and AI in agricultural systems. The review also aims to identify present trends, challenges, and opportunities in utilizing IoT and AI in agricultural systems. Diverse forms of agricultural practices are scrutinized to discern the applications of IoT and AI systems. Through a critical analysis of existing literature, this study contributes to a deeper understanding of how the integration of IoT and AI technologies can revolutionize PA, resulting in improved efficiency, sustainability, and productivity in the agricultural sector.
The Quasi-Resonant Structure and Control Strategy of a Photovoltaic Flyback Grid-Connected Microinverter
Authors: Cao Zipei , Jamali Annisa binti , Yassin Abdullah , Huang Ya
Published: May 2024

This study proposes a topology structure for a flyback grid-connected inverter with a compensation capacitor. The addition of the compensation capacitor structure increases the harmonic oscillation period and reduces the switching frequency. Additionally, a control strategy for the microinverter is proposed. By using an accurate peak current reference curve, the system ensures precise turn-off signals, thus reducing the harmonic content of the grid-connected current. Simultaneously, the multi-valley turn-on strategy is employed to address the issue of high switching frequency, minimising the impact of energy. The proposed topology structure and control methods are modelled, simulated, and tested to validate the feasibility of the microinverter topology structure and the effectiveness of the control strategy, achieving a maximum efficiency of 95.2% and controlling the total harmonic distortion (THD) below 2.39%. Compared to other microinverter products, it is more efficient and stable.
A Space Vector Modulation Strategy for Improving Voltage Transfer Ratio of Multi-Phase Inverter
Authors: Xia Yihui , Jing Mingchen , Ma Yuanzheng
Published: May 2024

In the five-phase-inverter adjustable speed system, a five-phase two-level inverter usually adopts the nearest-two vector SVPWM (NTV-SVPWM) or the nearest-four vector SVPWM (NFV-SVPWM). The former one has a high-output-current harmonic, which increases the power losses, while the latter one has a low harmonic, but its sinusoidal voltage transfer ratio (VTR) is 0.812, which decreases load capacity. To improve the loading capacity and decrease the power losses of the five-phase-inverter adjustable speed system, a new space vector over-modulation method based on multi-vector weighting is proposed in this paper, and harmonic characteristics of the proposed over-modulation method are analyzed. The simulation results indicate that the proposed over-modulation method has a lower output voltage error than that with the traditional NFV-SVPWM and has a lower output current THD than that with the traditional NTV-SVPWM. The experimental results verify that the proposed method is correct and feasible.
Time-Dependent Multi-Particle Model Describing the Hydrogen Absorption of Nanocrystalline Magnesium Powders: A Case Study
Authors: Révész Ádám , Pintér Áron
Published: May 2024

Classical kinetic models describing the hydrogen absorption of nanocrystalline metallic hydrides generally do not involve any parameter related to the change in the crystallite size during the hydrogenation at constant temperature. In the present investigation, ball-milled nanocrystalline Mg powders exhibiting lognormal crystallite size distribution have been subjected to hydrogen absorption in a Sievert-type apparatus. Partially absorbed states were achieved by interrupting the hydrogenation cycle at different hydrogen content, i.e., when 15%, 50%, and 90% of Mg powder transformed to MgH2. The evolution of the characteristic size of the nucleating MgH2 phase was determined from X-ray diffraction analysis. Considering the crystallite size distribution of the as-milled powder agglomerate as well as the growth during the isothermal hydrogenation process, a time-dependent multi-particle reaction function ∝CV¯t;R(t) was developed. It was shown unambiguously for this case study that the measured hydrogen absorption curve of the ball-milled Mg powder shows the best correlation with this model when it is compared to classical kinetic functions or the previously developed multi-particle reaction function excluding the change in the average crystallite size during hydrogenation.
Statistical Models for High-Risk Intestinal Metaplasia with DNA Methylation Profiling
Authors: Wang Tianmeng , Huang Yifei , Yang Jie
Published: May 2024

We consider the newly developed multinomial mixed-link models for a high-risk intestinal metaplasia (IM) study with DNA methylation data. Different from the traditional multinomial logistic models commonly used for categorical responses, the mixed-link models allow us to select the most appropriate link function for each category. We show that the selected multinomial mixed-link model (Model 1) using the total number of stem cell divisions (TNSC) based on DNA methylation data outperforms the traditional logistic models in terms of cross-entropy loss from ten-fold cross-validations with significant p-values 8.12×10−4 and 6.94×10−5. Based on our selected model, the significance of TNSC’s effect in predicting the risk of IM is justified with a p-value less than 10−6. We also select the most appropriate mixed-link models (Models 2 and 3) when an additional covariate, the status of gastric atrophy, is available. When the status is negative, mild, or moderate, we recommend Model 2; otherwise, we prefer Model 3. Both Models 2 and 3 can predict the risk of IM significantly better than Model 1, which justifies that the status of gastric atrophy is informative in predicting the risk of IM.
Reconfigurable-Intelligent-Surface-Enhanced Dynamic Resource Allocation for the Social Internet of Electric Vehicle Charging Networks with Causal-Structure-Based Reinforcement Learning
Authors: Zhang Yuzhu , Xu Hao
Published: May 2024

Charging stations and electric vehicle (EV) charging networks signify a significant advancement in technology as a frontier application of the Social Internet of Things (SIoT), presenting both challenges and opportunities for current 6G wireless networks. One primary challenge in this integration is limited wireless network resources, particularly when serving a large number of users within distributed EV charging networks in the SIoT. Factors such as congestion during EV travel, varying EV user preferences, and uncertainties in decision-making regarding charging station resources significantly impact system operation and network resource allocation. To address these challenges, this paper develops a novel framework harnessing the potential of emerging technologies, specifically reconfigurable intelligent surfaces (RISs) and causal-structure-enhanced asynchronous advantage actor–critic (A3C) reinforcement learning techniques. This framework aims to optimize resource allocation, thereby enhancing communication support within EV charging networks. Through the integration of RIS technology, which enables control over electromagnetic waves, and the application of causal reinforcement learning algorithms, the framework dynamically adjusts resource allocation strategies to accommodate evolving conditions in EV charging networks. An essential aspect of this framework is its ability to simultaneously meet real-world social requirements, such as ensuring efficient utilization of network resources. Numerical simulation results validate the effectiveness and adaptability of this approach in improving wireless network efficiency and enhancing user experience within the SIoT context. Through these simulations, it becomes evident that the developed framework offers promising solutions to the challenges posed by integrating the SIoT with EV charging networks.
Application of Model-Free and Model-Based Kinetic Methods in Evaluation of Reactions Complexity during Thermo-Oxidative Degradation Process: Case Study of [4-(Hydroxymethyl)phenoxymethyl] Polystyrene Resin
Authors: Janković Bojan , Dodevski Vladimir , Veljković Filip , Janković Marija , Manić Nebojša
Published: May 2024

This work examined the possibilities and limitations of model-free and model-based methods related to decrypting the kinetic complexity of multi-step thermo-oxidative degradation processes (as a testing system, a [4-(hydroxymethyl)phenoxymethyl] polystyrene resin was used), monitored by thermal analysis (TGA-DTG-DTA) techniques. It was found that isoconversional methods could successfully determine the correct number of process stages and presence of multiple reactions based on derived Ea(α) profiles and identify the negative dependence of the rate constant on the temperature. These methods could not overcome the problem that arose due to mass transfer limitations. The model-based method overcame more successfully the problem associated with mass transfer because its calculation machinery had capabilities for the correct solution of the total mass balance equation. However, a perfect fit with the experimental data was not achieved due to the dependence on the thermal history of the contribution (ctb.) of a given reaction step inside a fitting procedure cycle. On the other hand, through this approach, it was possible to estimate the rate-controlling steps of the process regarding the influence of the heating rate. It was found that for consecutive reaction mechanisms, the production of benzaldehyde and gases in high yields was controlled by the heating rate, where low heating rates were strongly recommended (≤10 K/min). Also, it was shown that the transport phenomenon may be also the rate-determining step (within the set of “intrinsic” kinetic parameters). It was also established that external heat transfer controls the overall rate, where the “pure” kinetic control regime had not been reached but was approached when lowering the temperature and size of the resin particles.
Slate–Cork Laminate Enhanced with Silicone for Habitat Industry Application
Authors: Abenojar Juana , López de Armentia Sara , Martínez Miguel Angel
Published: May 2024

This study investigates the feasibility of using a composite material comprising slate reinforced with cork sheets for architectural purposes like facades and wall coverings. The research involves the comprehensive characterisation of both slate and cork materials along with the evaluation of the silicone adhesive used in their bonding process, specifically Sikasil® HT from SIKA®. It was found that both slate and cork exhibited low wettability, which was enhanced through cold plasma treatment. Subsequently, a composite sandwich structure was fabricated and subjected to impact testing in a drop tower, along with fire resistance evaluations. The fire tests revealed that when subjected to a flame of 900 °C for 15 min, the slate alone heated rapidly, reaching 500 °C within 3 min on the side opposite to the flame. However, the sandwich structure reached 260 °C on the cork side (opposite to the flame) at 7.5 min, maintaining this temperature until the deterioration or detachment of the cork between 11 and 12 min. This provided insulation and delayed ignition. The sandwich structure maintained its fire resistance due to the insulating properties of cork and the superior thermal resistance of silicone compared to other adhesives up to 260 °C. Overall, the results suggest the potential suitability of this sandwich structure for architectural applications. Its favourable adhesion properties and acceptable fire resistance indicate that it could serve as a viable alternative for construction materials in architectural contexts.
Wind Tunnel Experiments on Parallel Blade–Vortex Interaction with Static and Oscillating Airfoil
Authors: Colli Andrea , Zanotti Alex , Gibertini Giuseppe
Published: May 2024

This study aims to experimentally investigate the effects of parallel blade–vortex interaction (BVI) on the aerodynamic performances of an airfoil, in particular as a possible cause of blade stall, since similar effects have been observed in literature in the case of perpendicular BVI. A wind tunnel test campaign was conducted reproducing parallel BVI on a NACA 23012 blade model at a Reynolds number of 300,000. The vortex was generated by impulsively pitching a second airfoil model, placed upstream. Measurements of the aerodynamic loads acting on the blade were performed by means of unsteady Kulite pressure transducers, while particle image velocimetry (PIV) techniques were employed to study the flow field over the blade model. After a first phase of vortex characterisation, different test cases were investigated with the blade model both kept fixed at different incidences and oscillating sinusoidally in pitch, with the latter case, a novelty in available research on parallel BVI, representing the pitching motion of a helicopter main rotor blade. The results show that parallel BVI produces a thickening of the boundary layer and can induce local flow separation at incidences close to the stall condition of the airfoil. The aerodynamic loads, both lift and drag, suffer important impulsive variations, in agreement with literature on BVI, the effects of which are extended in time. In the case of the oscillating airfoil, BVI introduces hysteresis cycles in the loads, which are generally reduced. In conclusion, parallel BVI can have a detrimental impact on the aerodynamic performances of the blade and even cause flow separation, which, while not being as catastrophic as in the case of dynamic stall, has relatively long-lasting effects.
Application of Different Animal Fats as Solvents to Extract Carotenoids and Capsaicinoids from Sichuan Chili
Authors: Zheng Bingyu , Wu Yida , Wang Yong , Li Ying
Published: May 2024

Inspired by the proved dissolving power of vegetable oils for non-polar and low-polar natural compounds, animal fats with triglycerides as the major components were investigated as food-grade solvents in this study for the simultaneous extraction of carotenoids and capsaicinoids from Sichuan chili. The dissolving power of lard, beef tallow, chicken fat and basa fish oil in the extraction of er jing tiao chili was firstly compared, where animal oils with worse extraction ratios for carotenoids (0.79 mg/g in average) performed better for the extraction of capsaicinoids (0.65 mg/g in average). Furthermore, the solvent effect of animal fats on the oleo-extracts was evaluated in terms of fatty acid composition, oil quality indexes, crystal polymorphism, melting and crystallization behaviors, where no significant differences were observed between animal fats before and after extraction. The oxidative stability of animal fats could be 1.02- up to 2.73-fold enhanced after extraction and the pungency degree could reach the same spicy level as commercial hotpot oil. In addition, the Hansen solubility parameters of solvents and solutes were predicted for further theoretical miscibility study, which helps to make a better comprehension of the dissolving mechanism behind such oleo-extraction. Overall, animal fats demonstrated their considerable solvent power for extracting carotenoids and capsaicinoids simultaneously from Sichuan chili, which showed significant potential for developing a novel Sichuan spicy hotpot oil with enhanced flavor and stability.
Osmolality and Tonicity of Isotonic Beverages
Authors: Skarlovnik Tjaša , Lamut Andraž , Hostnik Gregor , Gole Boris , Bren Urban
Published: May 2024

This study aimed to measure and compare the osmolality and tonicity of isotonic beverages that can be bought on the Slovenian market. The main goal was to examine how good is the agreement between the measured osmolalities of the beverages and the requirements for isotonic beverages set up by EFSA. Osmolalities were measured with an osmometer using the freezing point depression method. Afterwards, two complementary methods for the observation of tonicity were developed. Erythrocytes were exposed to standard NaCl solutions of different osmolalities to observe their influence on the volume and shape of cells following the turbidity of the solution and the morphology of erythrocytes. These two methods enabled us to determine whether standard solutions were hypo-, iso-, or hypertonic. In this way, we found that the osmolality of 12 out of the 18 investigated isotonic beverages was in the range of 270–330 mOsm/kg, as required by EFSA. However, six samples did not meet this criterion and should therefore not have the label “isotonic” or be described as such. The measurements of turbidity of solutions indicated that most isotonic beverages exhibit a lower tonicity than standard NaCl solutions of identical osmolality. However, examination of the erythrocytes in isotonic beverages showed that the measurements were additionally complicated by the low pH values of these beverages. Finally, by demonstrating how different components of isotonic beverages pass through the erythrocyte membranes, we found that even isoosmolal beverages are often not isotonic, as the concentration of actively transported sugars in these beverages is relatively high.
Insights into the Volatile Flavor Profiles of Two Types of Beef Tallow via Electronic Nose and Gas Chromatography–Ion Mobility Spectrometry Analysis
Authors: Li Ke , Zhang Liangyao , Yi Danhui , Luo Yunxiao , Zheng Chao , Wu Yinglong
Published: May 2024

In the current study, an electronic nose (E-nose) and gas chromatography–ion mobility spectrometry (GC-IMS) were employed to investigate the volatile flavor compounds (VFCs) of intense flavor beef tallow (L) and ordinary beef tallow (P). The study results indicate that an E-nose combined with an LDA and GC-IMS combined with an OPLS-DA can effectively distinguish between the two types of beef tallow. Compared with ordinary beef tallow, the E-nose sensors of intense flavor beef tallow have stronger response signals to sulfides, terpenes, and nitrogen oxides. A total of 22 compounds contribute to making the flavor of intense flavor beef tallow more typical and richer; in contrast, ethyl acetate was the main aroma-active compound found in the ordinary beef tallow. Sulfur-containing compounds and terpenoids might be the key substances that cause sensory flavor differences between the two types of beef tallow. In conclusion, the results of this study clarify the characteristics and differences of the two types of beef tallow and provide an enhanced understanding of the differences in the flavors of the two types of beef tallow.
Volatile Constituents of Some Myrtaceous Edible and Medicinal Fruits from the Brazilian Amazon
Authors: Barroso Adenilson S. , Massing Lais T. , Suemitsu Chieno , Mourão Rosa Helena V. , Figueiredo Pablo Luis B. , Maia José Guilherme S.
Published: May 2024

Native and exotic fruits from the Amazon have varied characteristics, with aroma being a decisive factor in their acceptance for medicinal use as a nutraceutical supplement. This work aimed to analyze the chemical constituents of the volatile concentrates of some Myrtaceous fruit species sampled in the Brazilian Amazon. The fruit’s pulps were subjected to simultaneous distillation–extraction, and gas chromatography–mass spectrometry was used to analyze their volatile chemical composition. In the volatile concentrate of Eugenia stipitata (Araçá-boi) α-pinene (17.5%), citronellyl butanoate (15.6%), and pogostol (13.5%) were identified as primary constituents; Eugenia uniflora (Ginja) concentrate comprised curzerene (30.5%), germacrone (15.4%), atractylone (13.1%), and (E)-β-ocimene (11.1%); in Myrciaria dubia (Camu-Camu), α-pinene (55.8%), (E)-β-ocimene (13.1%), and α-terpineol (10.0%) were present; in Psidium guajava (Goiaba) were (2E)-hexenal (21.7%), hexanal (15.4%), caryophylla-4(12),8(13)-dien-5-β-ol (10.5%), caryophyllene oxide (9.2%), and pogostol (8.3%); and in Psidium guineense (Araçá), limonene (25.2%), ethyl butanoate (12.1%), epi-β-bisabolol (9.8%), and α-pinene (9.2%) were the main constituents. The analyzed volatile concentrates of these fruit species presented a significant diversity of constituents with a predominance of functional groups, such as monoterpenes, sesquiterpenes, and fatty acid derivatives, originating from the plant’s secondary metabolism and playing an important role in their nutritional and medicinal uses.
Dried Beetroots: Optimization of the Osmotic Dehydration Process and Storage Stability
Authors: Šuput Danijela , Rakita Slađana , Spasevski Nedeljka , Tomičić Ružica , Dragojlović Danka , Popović Senka , Hromiš Nevena
Published: May 2024

In this study, beetroots were osmotically dehydrated in sugar beet molasses. The input parameters of the drying process were varied: temperature (20 °C, 40 °C, and 60 °C), time (1 h, 3 h, and 5 h), and concentration of sugar beet molasses (40%, 60%, and 80%). Basic quality indicators were determined for the dried beetroot samples: dry matter content, water loss, solid gain, mineral and betaine content, and phenols and flavonoids, as well as antioxidant potential. After optimizing the results, favorable drying parameters were selected: temperature 60 °C, molasses concentration 70%, and processing time 5 h. According to the optimal drying conditions, the beetroots were dried and stored at 4 °C for 28 days. Half of the dried samples were coated with an edible biopolymer coating based on Camelina sativa oilcake, while the other half of the samples remained uncoated. The sustainability study aimed to confirm the effects of the biopolymer coating on the quality and sustainability of the osmotically dried beetroots.
Effect of Lactiplantibacillus plantatum HFY11 on Colitis in Mice
Authors: Tan Fang , Zhou Xianrong , Ren Lixuan , Kong Chang-Suk
Published: May 2024

This study aimed to examine the potential impact of the intervention of Lactiplantibacillus plantatum HFY11 (LP-HFY11) on colitis using in vivo animal trials. The impact of LP-HFY11 intervention on colitis was determined by measuring the levels of relevant indicators in the intestine, colon, and blood after oxazolone-induced colitis in BALB/c mice. The results of the trial show that LP-HFY11 improved the colon weight-to-length ratio, reduced the colitis-induced colon length shortening, and reduced colonic abstinence. Furthermore, it decreased the levels of myeloperoxidase, nitric oxide, and malondialdehyde activities while increasing the glutathione content in the colon tissue of colitis-affected animals. LP-HFY11 lowered the interleukin-10 (IL-10) level and increased the IL-2 level in the serum of colitis mice. LP-HFY11 also upregulated the expression of neuronal nitric oxide synthase, endothelial nitric oxide synthase, c-Kit, and stem cell factor (SCF), and downregulated the expression of IL-8, C-X-C chemokine receptor type 2 (CXCR2), and inducible nitric oxide synthase (iNOS) in the colon tissue of mice with colitis. LP-HFY11 decreased the expression of Firmicutes in the gut while increasing the expression of Bacteroidetes, Bifidobacteria, and Lactobacillus. This indicates that LP-HFY11 could control physiological alterations in the serum and colon tissue, as well as the expression of gut microorganism.
Arsenic, Cadmium, and Lead Levels in School Meals and Their Risk Assessment in Municipalities in Bahia, Brazil
Authors: Santos Larissa da S. , Chagas Fabiana F. , Martinho Martinho G. Dinis , Gomes-Júnior Erival A. , Silva Mariângela V. Lopes , Menezes-Filho José A.
Published: May 2024

Background: School meals represent a significant supply of nutrients for children in Brazil, especially those in conditions of social vulnerability. Objectives: This study aimed to assess the levels of arsenic (As), cadmium (Cd), and lead (Pb) in meals served in public elementary schools in four municipalities in the state of Bahia, Brazil, and assess the risk posed to children’s health. Methods: Ninety-six samples were collected from 16 schools, freeze-dried, and subjected to microwave-assisted digestion. The As, Cd, and Pb levels were determined by graphite furnace atomic absorption spectrometry. The risk assessment was based on calculating each element’s hazard quotient (HQ). Results: None of the samples reached or exceeded the tolerable levels for the elements analyzed. Pb was the metal that obtained the most significant result, reaching maximum levels of 39–157 µg·kg−1. Conclusions: No element exceeded the PTWI proposed by JECFA; thus, the toxic metal content in school meals poses a negligible risk to children’s health.
A Review of the Impact of Starch on the Quality of Wheat-Based Noodles and Pasta: From the View of Starch Structural and Functional Properties and Interaction with Gluten
Authors: Wang Jinrong , Li Yonghui , Guo Xiaona , Zhu Kexue , Wu Zijian
Published: May 2024

Starch, as a primary component of wheat, plays a crucial role in determining the quality of noodles and pasta. A deep understanding of the impact of starch on the quality of noodles and pasta is fundamentally important for the industrial progression of these products. The starch structure exerts an influence on the quality of noodles and pasta by affecting its functional attributes and the interaction of starch–gluten proteins. The effects of starch structure (amylopectin structure, amylose content, granules size, damaged starch content) on the quality of noodles and pasta is discussed. The relationship between the functional properties of starch, particularly its swelling power and pasting properties, and the texture of noodles and pasta is discussed. It is important to note that the functional properties of starch can be modified during the processing of noodles and pasta, potentially impacting the quality of the end product, However, this aspect is often overlooked. Additionally, the interaction between starch and gluten is addressed in relation to its impact on the quality of noodles and pasta. Finally, the application of exogenous starch in improving the quality of noodles and pasta is highlighted.
Changes in α-Dicarbonyl Compound Contents during Storage of Various Fruits and Juices
Authors: Yang Yang , Liu Xue-Yi , Zhao Qian , Wu Dan , Ren Jin-Tao , Ma Meng , Li Pei-Yun , Wu Jia-Cai , Gao Wen-Yun , Li Heng
Published: May 2024

α-Dicarbonyl compounds (α-DCs) are commonly present in various foods. We conducted the investigation into concentration changes of α-DCs including 3-deoxyglucosone (3-DG), glyoxal (GO), and methylglyoxal (MGO) in fresh fruits and decapped commercial juices during storage at room temperature and 4 °C, as well as in homemade juices during storage at 4 °C. The studies indicate the presence of α-DCs in all samples. The initial contents of 3-DG in the commercial juices (6.74 to 65.61 μg/mL) are higher than those in the homemade ones (1.97 to 4.65 μg/mL) as well as fruits (1.58 to 3.33 μg/g). The initial concentrations of GO and MGO are normally less than 1 μg/mL in all samples. During storage, the α-DC levels in the fruits exhibit an initial increase followed by a subsequent decrease, whereas, in all juices, they tend to accumulate continuously over time. As expected, 4 °C storage reduces the increase rates of the α-DC concentrations in most samples. From the viewpoint of the α-DC contents, fruits and homemade juices should always be the first choice for daily intake of nutrients and commercial juices ought to be mostly avoided.
Fabricating Pea Protein Micro-Gel-Stabilized Pickering Emulsion as Saturated Fat Replacement in Ice Cream
Authors: Qin Xv , Guo Yaxian , Zhao Xiaoqing , Liang Bin , Sun Chanchan , Li Xiulian , Ji Changjian
Published: May 2024

Unsaturated fat replacement should be used to reduce the use of saturated fat and trans fatty acids in the diet. In this study, pea protein micro-gels (PPMs) with different structures were prepared by microparticulation at pH 4.0–7.0 and named as PPM (pH 4.0), PPM (pH 4.5), PPM (pH 5.0), PPM (pH 5.5), PPM (pH 6.0), PPM (pH 6.5), and PPM (pH 7.0). Pea protein was used as a control to evaluate the structure and interfacial properties of PPMs by particle size distribution, Fourier transform infrared spectroscopy (FTIR), free sulfhydryl group content, and emulsifying property. PPM (pH 7.0) was suitable for application in O/W emulsion stabilization because of its proper particle size, more flexible structure, high emulsifying activity index (EAI) and emulsifying stability index (ESI). The Pickering emulsion stabilized by PPM (pH 7.0) had a uniform oil droplet distribution and similar rheological properties to cream, so it can be used as a saturated fat replacement in the manufacture of ice cream. Saturated fat was partially replaced at different levels of 0%, 20%, 40%, 60%, 80%, and 100%, which were respectively named as PR0, PR20, PR40, PR60, PR80, and PR100. The rheological properties, physicochemical indexes, and sensory properties of low-saturated fat ice cream show that PPM (pH 7.0)-stabilized emulsion can be used to substitute 60% cream to manufacture low-saturated fat ice cream that has high structural stability and similar melting properties, overrun, and sensory properties to PR0. The article shows that it is feasible to prepare low-saturated fat ice cream with PPM (pH 7.0)-stabilized Pickering emulsion, which can not only maintain the fatty acid profile of the corn oil used, but also possess a solid-like structure. Its application is of positive significance for the development of nutritious and healthy foods and the reduction of chronic disease incidence.
Impact of Nanoencapsulated Rosemary Essential Oil as a Novel Feed Additive on Growth Performance, Nutrient Utilization, Carcass Traits, Meat Quality and Gene Expression of Broiler Chicken
Authors: Adil Sheikh , Banday Mohammad T. , Hussain Syed A. , Wani Manzoor A. , Al-Olayan Ebtesam , Patra Amlan K. , Rasool Shahid , Gani Adil , Sheikh Islam U. , Khan Azmat A. , Muzamil Showkeen
Published: May 2024

This study evaluated the effect of free and nanoencapsulated rosemary essential oil (REO) as an antibiotic alternative in broiler diets on growth performance, nutrient digestibility, carcass traits, meat quality and gene expression. Four hundred twenty day-old commercial broiler chicks (VENCOBB) were randomly allocated to seven dietary treatments, each having four replicates of fifteen chicks. The dietary treatments comprised control (CON) fed a basal diet only, AB (basal diet + 10 mg enramycin/kg), CS (basal diet + 150 mg chitosan nanoparticles/kg), REOF100 and REOF200 (basal diet + 100 mg and 200 mg free REO/kg, respectively), and REON100 and REON200 (basal diet + 100 mg and 200 mg nanoencapsulated REO/kg, respectively). Overall (7–42 d), REON200 showed the highest (p < 0.001) body weight gain (1899 g/bird) and CON had the lowest gain (1742 g/bird), while the CS, REOF100 and REOF200 groups had a similar gain, but lower than that of the AB and REON100 groups. Feed intake was not affected by dietary treatments. Overall, the feed efficiency increased (p = 0.001) by 8.47% in the REON200 group and 6.21% in the AB and REON100 groups compared with the CON. Supplementation of REO improved (p < 0.05) dry matter and crude protein digestibility, with the highest values in REON100 and REON200. Ether extract, crude fiber, calcium and phosphorus digestibility values showed no difference among the groups. The dressing, breast, thigh % increased (p < 0.05) and abdominal fat % decreased (p < 0.001) more in the REON200 group than with other treatments and CON. In breast meat quality, water holding capacity and extract reserve volume increased (p < 0.05) while drip loss and cholesterol content decreased (p < 0.05) in REON100 and REON200. No change was observed in the breast meat color among dietary treatments and CON. The REON100 and REON200 groups had reduced (p < 0.05) meat lipid peroxidation as depicted by the decreased levels of TBARS, free fatty acids and peroxide value compared to other treatments and CON. The expression of the Mucin 2, PepT1 and IL-10 genes was upregulated (p < 0.001) and TNF-α downregulated (p < 0.001) by dietary addition of REO particularly in the nanoencapsulated form compared with the CON. In conclusion, nanoencapsulated REO, especially at 200 mg/kg diet, showed promising results as an antibiotic alternative in improving the performance, nutrient digestibility, carcass traits, meat quality and upregulation of growth and anti-inflammatory genes.
Time-Delay Effects on the Collective Resonant Behavior in Two Coupled Fractional Oscillators with Frequency Fluctuations
Authors: He Minyue , Wang Huiqi , Lin Lifeng
Published: May 2024

In this study, we propose coupled time-delayed fractional oscillators with dichotomous fluctuating frequencies and investigate the collective resonant behavior. Firstly, we obtain the condition of complete synchronization between the average behavior of the two oscillators. Subsequently, we derive the precise analytical expression of the output amplitude gain. Based on the analytical results, we observe the collective resonant behavior of the coupled time-delayed system and further study its dependence on various system parameters. The observed results underscore that the coupling strength, fractional order, and time delay play significant roles in controlling the collective resonant behavior by facilitating the occurrence and optimizing the intensity. Finally, numerical simulations are also conducted and verify the accuracy of the analytical results.
Geostatistical Analysis of Lineament Domains: The Study Case of the Apennine Seismic Province of Italy
Authors: Cianfarra Paola , Morelli Danilo , Salvini Francesco
Published: May 2024

Regional-scale swarms of subparallel linear topographic features, known as lineament domains, are a common feature of planetary surfaces. Lineament domains are superficial manifestations of the crustal stress field trajectory. Notably, one of the effects of active tectonics is seismicity. Italy is one of the most seismically active regions in the Mediterranean, with many destructive earthquakes that have occurred in past centuries. Here, we assess the seismic meaning of the main lineament domain in the tectonically active region of Central Italy. We describe the use of an automated analysis of satellite imagery coupled with spatial grid analysis to identify three lineament domains of the Central Apennines. Spatial and azimuthal comparisons of the main lineament domain (i.e., the Apennine Domain), with the known locations of earthquakes (moment magnitude of Mw > 5.5) that occurred during the past century, revealed the most seismically active tectonic areas and their spatial distributions. Further, we present a conceptual seismo-geodynamic model for the Central Apennines, which is characterized by regional arching and explains the presence of an extensional tectonic regime in the upper crustal layer of the active Apennines fold-and-thrust belt.
Leveraging Transfer Learning and U-Nets Method for Improved Gap Filling in Himawari Sea Surface Temperature Data Adjacent to Taiwan
Authors: Putra Dimas Pradana , Hsu Po-Chun
Published: May 2024

Satellite sea surface temperature (SST) images are valuable for various oceanic applications, including climate monitoring, ocean modeling, and marine ecology. However, cloud cover often obscures SST signals, creating gaps in the data that reduce resolution and hinder spatiotemporal analysis, particularly in the waters near Taiwan. Thus, gap-filling methods are crucial for reconstructing missing SST values to provide continuous and consistent data. This study introduces a gap-filling approach using the Double U-Net, a deep neural network model, pretrained on a diverse dataset of Level-4 SST images. These gap-free products are generated by blending satellite observations with numerical models and in situ measurements. The Double U-Net model excels in capturing SST dynamics and detailed spatial patterns, offering sharper representations of ocean current-induced SST patterns than the interpolated outputs of Data Interpolating Empirical Orthogonal Functions (DINEOFs). Comparative analysis with buoy observations shows the Double U-Net model’s enhanced accuracy, with better correlation results and lower error values across most study areas. By analyzing SST at five key locations near Taiwan, the research highlights the Double U-Net’s potential for high-resolution SST reconstruction, thus enhancing our understanding of ocean temperature dynamics. Based on this method, we can combine more high-resolution satellite data in the future to improve the data-filling model and apply it to marine geographic information science.
A Comparative Analysis of the Bayesian Regularization and Levenberg–Marquardt Training Algorithms in Neural Networks for Small Datasets: A Metrics Prediction of Neolithic Laminar Artefacts
Authors: Troiano Maurizio , Nobile Eugenio , Mangini Fabio , Mastrogiuseppe Marco , Conati Barbaro Cecilia , Frezza Fabrizio
Published: May 2024

This study aims to present a comparative analysis of the Bayesian regularization backpropagation and Levenberg–Marquardt training algorithms in neural networks for the metrics prediction of damaged archaeological artifacts, of which the state of conservation is often fragmented due to different reasons, such as ritual, use wear, or post-depositional processes. The archaeological artifacts, specifically laminar blanks (so-called blades), come from different sites located in the Southern Levant that belong to the Pre-Pottery B Neolithic (PPNB) (10,100/9500–400 cal B.P.). This paper shows the entire procedure of the analysis, from its normalization of the dataset to its comparative analysis and overfitting problem resolution.
Cyclic Air Braking Strategy for Heavy Haul Trains on Long Downhill Sections Based on Q-Learning Algorithm
Authors: Zhang Changfan , Zhou Shuo , He Jing , Jia Lin
Published: May 2024

Cyclic air braking is a key factor affecting the safe operation of trains on long downhill sections. However, a train’s cycle braking strategy is constrained by multiple factors such as driving environment, speed, and air-refilling time. A Q-learning algorithm-based cyclic braking strategy for a heavy haul train on long downhill sections is proposed to address this challenge. First, the operating environment of a heavy haul train on long downhill sections is designed, considering various constraint parameters, such as the characteristics of special operating routes, allowable operating speeds, and train tube air-refilling time. Second, the operating status and braking operation of a heavy haul train on long downhill sections are discretized in order to establish a Q-table based on state–action pairs. The training of algorithm performance is achieved by continuously updating Q-tables. Finally, taking the heavy haul train formation as the study object, actual line data from the Shuozhou–Huanghua Railway are used for experimental simulation, and different hyperparameters and entry speed conditions are considered. The results show that the safe and stable cyclic braking of a heavy haul train on long downhill sections is achieved. The effectiveness of the Q-learning control strategy is verified.
A Neoteric Approach toward Social Media in Public Health Informatics: A Narrative Review of Current Trends and Future Directions
Authors: Awan Asma Tahir , Gonzalez Ana Daniela , Sharma Manoj
Published: May 2024

Social media has become more popular in the last few years. It has been used in public health development and healthcare settings to promote healthier lifestyles. Given its important role in today’s culture, it is necessary to understand its current trends and future directions in public health. This review aims to describe and summarize how public health professionals have been using social media to improve population outcomes. This review highlights the substantial influence of social media in advancing public health objectives. The key themes explored encompass the utilization of social media to advance health initiatives, monitor diseases, track behaviors, and interact with communities. Additionally, it discusses potential future directions on how social media can be used to improve population health. The findings show how social media has been used as a tool for research, implementing health campaigns, and health promotion. Social media integration with artificial intelligence (AI) and Generative Pre-Trained Transformers (GPTs) can impact and offer an innovative approach to tackle the problems and difficulties in health informatics. The research shows how social media will keep growing and evolving and, if used effectively, has the potential to help close public health gaps across different cultures and improve population health.
Discovery of the Larvae and Pupae of the Black Fly Simulium (Gomphostilbia) khelangense and Breeding Habitats of Potential Pest Species of the S. (G.) chumpornense Subgroup (Simuliidae)
Authors: Thanee Isara , Jumpato Waraporn , Jaroenchaiwattanachote Chavanut , Gomontean Bhuvadol , Wannasingha Wannachai , Namtaku San , Adler Peter H. , Pramual Pairot
Published: May 2024

Two species of black flies (Simuliidae) in Thailand, Simulium chumpornense Takaoka and Kuvangkadilok, 2000, and S. khelangense Takaoka, Srisuka & Saeung, 2022, are potent vectors of avian blood protozoa of the genera Leucocytozoon and Trypanosoma and are pests of domestic avian species. Although the adults are abundant throughout Thailand, information on their breeding habitats is limited, and the immature stages of S. khelangense are unknown. We collected the larvae and pupae of S. khelangense from the Mekong River, the first-ever record of Simuliidae from this large continental river. Mitochondrial cytochrome c oxidase I and internal transcribed spacer 2 were used to associate the larvae and pupae with known adults. Both genetic markers strongly supported their identity as S. khelangense. The larvae and pupa of S. khelangense are described. The pupal gill filaments, larval abdominal protuberances, and setae distinguish this species from other members of the S. varicorne species group. The immature stages of S. chumpornense inhabit a wide variety of flowing waters, from small streams (3 m wide) to enormous continental rivers (400 m wide); thus, S. chumpornense is a habitat generalist. In contrast, S. khelangense was found only in the large Mekong River and is, therefore, a habitat specialist. Both species can exploit their principal habitats and produce abundant adult populations.
Risk Assessment of Spodoptera exempta against Food Security: Estimating the Potential Global Overlapping Areas of Wheat, Maize, and Rice under Climate Change
Authors: Li Ming , Jin Zhenan , Qi Yuhan , Zhao Haoxiang , Yang Nianwan , Guo Jianyang , Chen Baoxiong , Xian Xiaoqing , Liu Wanxue
Published: May 2024

Spodoptera exempta, known as the black armyworm, has been extensively documented as an invasive agricultural pest prevalent across various crop planting regions globally. However, the potential geographical distribution and the threat it poses to host crops of remains unknown at present. Therefore, we used an optimized MaxEnt model based on 841 occurrence records and 19 bioclimatic variables to predict the potential suitable areas of S. exempta under current and future climatic conditions, and the overlap with wheat, rice, and maize planting areas was assessed. The optimized model was highly reliable in predicting potential suitable areas for this pest. The results showed that high-risk distribution areas for S. exempta were mainly in developing countries, including Latin America, central South America, central Africa, and southern Asia. Moreover, for the three major global food crops, S. exempta posed the greatest risk to maize planting areas (510.78 × 104 km2), followed by rice and wheat planting areas. Under future climate scenarios, global warming will limit the distribution of S. exempta. Overall, S. exempta had the strongest effect on global maize production areas and the least on global wheat planting areas. Our study offers a scientific basis for global prevention of S. exempta and protection of agricultural crops.