bluuebunny/crossref_metadata_2025 huggingface dataset:
Cost of Energy Consumption and Return of Excise Tax on Motor Fuels vs. the Durability of Operations and Financial Sustainability in Polish Agriculture
Authors: Kulawik Jacek , Soliwoda Michał , Kurdyś-Kujawska Agnieszka , Herda-Kopańska Justyna , Klimkowski Cezary
Published: December 2023

For the European Union, the course of the Community’s energy and climate policy as well as changes in the objectives and priorities of the Common Agricultural Policy, as reflected, among others, in rural development programs subject to ex ante, environmental and ex post evaluation, should be considered. Individual EU countries are still implementing their own programs focused on improving energy efficiency, energy modernisation and supporting renewable energy, and they also intervene in the energy market on an ad hoc basis, as was the case after the outbreak of the war in Ukraine. This article fits into such a broadly understood research perspective, and its primary goal is to identify the impact of the costs of energy consumption and the reimbursement of excise tax on motor fuels on the operational durability and financial sustainability of 103 farms belonging to the Polish FADN network, which in 2017–2021 implemented modernisation projects under the rural development program. Logistic and linear multivariate regression were used to estimate the strength, direction and significance of correlation relationships. It was found that relative energy costs were significantly negatively correlated with financial sustainability only in the linear model, while the impact of excise tax return was positive but not significant. Thus, an empirical proof of the advisability of a possible public intervention aimed at making farmers’ access to energy cheaper was obtained. All public interventions in agricultural energy use should be subject to careful and systematic ex ante, mid-term and ex post assessments based on sound program theory. It is necessary to identify the cause-and-effect chains, in which the regression proposed in the article may be helpful.
Multiphysics Simulation of a Novel Self-Adaptive Chip Cooling with a Temperature-Regulated Metal Pillar Array in Microfluidic Channels
Authors: Xiang Liyin , Yang Rui , Zhang Dejun , Zhou Xiaoming
Published: December 2023

Conventional liquid cooling techniques may provide effective chip cooling but at the expense of high pumping power consumption. Considering that there is dynamic heat load in practice, a self-adaptive cooling technique is desired to reduce operational costs while preserving inherent cooling effectiveness. In this work, a novel self-adaptive cooling strategy is presented to balance the thermal and flow efficiency in accordance with the dynamic thermal load, based on temperature-regulated movement of the metal pillar array in a microfluidic channel. With an illustrative device, the effectiveness of such a strategy is investigated using multiphysics modeling and simulation. As a case study, the device is considered to be initiated with a chip power of 5 W and an inlet coolant velocity of 0.3 m/s. It is shown that the temperature-regulated movement of the metal pillar heat sink will be activated rapidly and equilibrate within 30 s. Parts of the metal pillars immerse into the coolant flow, resulting in significantly improved heat transfer efficiency. The diminished thermal resistance leads to a reduction in chip temperature rise from 225 K (without structural adaptation) to 91.86 K (with structural adaption). Meanwhile, the immersion of metal pillars into the coolant also causes an increased flow resistance in the microfluidic channel (i.e., pressure drop increases from 859.27 Pa to 915.98 Pa). Nevertheless, the flow resistance decreases spontaneously when the working power of the chip decreases. Comprehensive simulation has demonstrated that the temperature-regulated structure works well under various conditions. Therefore, it is believed that the presented self-adaptive cooling strategy offers simple and cost-effective thermal management for modern electronics with dynamic heat fluxes.
Technical Implications of the Use of Biofuels in Agricultural and Industrial Compression-Ignition Engines with a Special Focus on the Interactions with (Bio)lubricants
Authors: Piri Homeyra , Renzi Massimiliano , Bietresato Marco
Published: December 2023

The environmental sustainability of agricultural and industrial vehicles, as well as of the transportation sector, represents one of the most critical challenges to the sustainable development of a nation. In recent decades, compression-ignition engines have been widely used in on-road and off-road vehicles due to their better fuel economy, autonomy, compactness, and mechanical performance (spec. the high torque values). Due to the consistent environmental impact of fossil fuels, scientists are searching for alternative energy sources while preserving the beneficial features of diesel engines. The utilization of blends of diesel fuel, biodiesel, and bioethanol fuel (referred to as “ternary blends”) is among the most promising solutions for replacing fossil fuels in the near term, allowing, at the same time, us to continue using existing vehicles until new technologies are developed, consolidated and adapted to the agricultural and industrial sector. These ternary blends can lower exhaust emissions without creating major problems for existing fuel-feeding systems, typically designed for low-viscosity fossil fuels. One of the concerns in using liquid biofuels, specifically biodiesel, is the high chemical affinity with conventional and bio-based lubricants, so the main parameters of lubricants can vary significantly after a long operation of the engine. The comprehensive literature review presented in this article delves into the technical challenges, the main research pathways, and the potential solutions associated with the utilization of biofuels. Additionally, it investigates the emerging application of nanoparticles as additives in lubricants and biofuels, highlighting their valuable potential. This study also discusses the potential implementation of bio-ethanol in ternary blends, offering a promising avenue for reducing reliance on fossil fuels while maintaining engine efficiency.
Estimation of the Transverse Wave Velocity in Siliceous Carbonate Reservoirs of the Dengying Formation in the Gaoshiti–Moxi Area, Sichuan Basin, China
Authors: Xue Lian , Zhu Zhengping , Weng Xuebo , Pan Renfang , Shi Jinxiong
Published: December 2023

Siliceous minerals of the Dengying Formation in the Gaoshiti–Moxi area in the central Sichuan Basin exhibit four types of quartz crystals (cryptocrystalline quartz, chalcedony, microcrystalline quartz, and megacrystalline quartz) and three structural types: cryptocrystalline, microcrystalline, and mosaic (laminated mosaic, window-hole interrupted mosaic, and arc-laminated mosaic). Siliceous minerals have a great influence on the storage performance of the reservoirs in the Dengying Formation. According to the petrophysical parameters of the Dengying Formation and porosity intersection diagrams, the siliceous dolomite and the reservoirs have low impedance characteristics, which makes it difficult to distinguish between them and leads to difficulties in the characterization and prediction of the reservoirs. The transverse wave velocity is favorable for reservoir characterization. Currently, the main method used to estimate the transverse wave velocity is petrophysical modeling, which establishes a relationship between the elastic and physical parameters of the reservoir. In this paper, the siliceous minerals in the dolomite in the study area are regarded as solid inclusions, and the calculation method of the rock matrix modulus is improved by using solid replacement. Then, an improved petrophysical model is constructed by combining the KT (Kuster–Toksöz) model, the DEM (Discrete Element Method) model, the Gassmann equation, and the Wood equation. The transverse wave velocity is estimated using the improved model under the constraint of the longitudinal wave velocity. The shapes of the transverse wave velocity curves obtained by the improved model and the deviations from the measured velocities are significantly better than those of the Xu–Payne model and other models. The results show that the improved model can effectively estimate the transverse wave velocity of the reservoir in this area, which provides a basis for future reservoir predictions in this area.
Comparison of Surface Roughness of Beech Wood after Sanding with an Eccentric and Belt Sander
Authors: Adamčík Lukáš , Dzurenda Ladislav , Banski Adrián , Kminiak Richard
Published: December 2023

The presented paper deals with a mutual comparison of the roughness of the sanded radial surface after an eccentric and a belt sander. The beech wood (Fagus sylvatica L.) was sanded with an eccentric sander ETS 125 REQ-PLUS and a belt sander BS-75 E-set from Festool with the grit sizes P40, P60, P80, P100, P120 and P150. The evaluation of the roughness parameters Ra, Rp, Rv, Rz, and Rt was carried out using a digital microscope with a 2.5 mm L-filter and an 8 μm S-filter under the conditions of the technical standard STN EN ISO 21920. The measured results were supported using microscopic analysis of the surface topography especially for surfaces with very high roughness. The experiment shows a lower surface roughness of beech wood sanded with an eccentric sander. The sander created a surface with smaller grooves, removed more protruding fibers and created a more homogeneous surface suitable for subsequent surface treatment.
Influence of Irrigation on Biomass Partitioning in Above- and Belowground Organs of Trees Planted in Desert Sites of Mongolia
Authors: Byambadorj Ser-Oddamba , Park Byung Bae , Lkhagvasuren Sarangua , Tsedensodnom Enkhchimeg , Byambasuren Otgonsaikhan , Khajid Altankhundaga , Chiatante Donato , Nyam-Osor Batkhuu
Published: December 2023

Planting trees is considered a crucial factor in mitigating the increase in carbon emissions in the atmosphere by generating plant biomass. In addition to advancing our understanding of how tree biomass is allocated in desert environments, we explore potential variations in biomass partitioning based on the irrigation regimes (4, 8, and 12 L h−1) supporting the growth of these trees. Specifically, this study compares the pattern of biomass distribution between above-ground and belowground organs of 11-year-old trees (U. pumila, E. moorcroftii, and T. ramosissima) planted in a desert site in Mongolia. An interesting result of this study is the demonstration that biomass partitioning among roots of different diameter classes differs between the tree species tested, suggesting that each tree species establishes its own type of root/soil interaction. The differences in biomass partitioning in roots could determine specificity in the strength of anchorage and efficiency of nutrition for the trees. We also demonstrate that the presence of plantations influences certain chemical properties of the desert soil, with differences depending on the tree species planted. In addition to presenting a method for planting trees in desert sites, this study underscores that a reliable evaluation of atmospheric carbon sequestration in trees must necessarily include root excavation to obtain an accurate measurement of biomass stored in belowground structures. Assessing the overall biomass produced by these trees allows us to determine the potential for carbon sequestration achievable through plantations established in desert sites.
Soil Microbial Communities in Pseudotsuga sinensis Forests with Different Degrees of Rocky Desertification in the Karst Region, Southwest China
Authors: Li Wangjun , He Bin , Feng Tu , Bai Xiaolong , Zou Shun , Chen Yang , Yang Yurong , Wu Xuefeng
Published: December 2023

Rocky desertification (RD), a natural and human-induced process of land degradation in karst areas, has become the primary ecological disaster and one of the obstacles to sustainable ecological development in southwest China. Nevertheless, the variation of soil physical and chemical properties, bacterial and fungal communities, and their relationships in RD forests remains limited. Therefore, soil samples were collected from forests under four degrees of RD (NRD, non-RD; LRD, light RD; MRD, moderate RD; and SRD, severe RD) and subjected to high-throughput sequencing of 16S rRNA and ITS1 genes. The results showed a significant reduction in bacterial richness and diversity, while fungal richness and diversity decreased markedly and then showed a balanced trend with the increase in RD degree, indicating that bacteria and fungi did not present the same dynamics in response to the process of RD. The bacterial communities were dominated by Proteobacteria, Actinobacteria, Acidobacteria, and Chloroflexi, while the fungal communities were dominated by Basidiomycota, Ascomycota, and Mortierellomycota. The PCoA and NMDS demonstrated significant differences in microbial communities in study sites, among which the fungal communities in non-RD forest and LRD forest clustered together, suggesting that fungal communities were more stable than bacteria in RD forest. The db-RDA, Mantel test, and random forest model confirmed the important role of soil BD, pH, SOC, AN, and AP in driving microbial diversity and communities. The IndVal analysis suggested that Chloroflexi, Patescibacteria, Atheliales, and Cantharellales with high indicator values were identified as potential bio-indicators for RD forests. This study could not only improve our understanding of bacterial and fungal community dynamics across RD gradients, but also could provide useful information for the further use of microorganisms as indicators to reflect the environmental changes and ecosystem status during forest RD.
The Diversity and Community Pattern of Liverworts on Sygera Mountain, Tibet
Authors: Song Xiaotong , Gu Jiqi , Ye Yanhui , Li Wei , Liao Yujia , Wang Ruihong , Ma Heping , Shao Xiaoming
Published: December 2023

Elevation has been a cornerstone of biodiversity research, and changes in the environmental factors behind it influence biodiversity and community patterns. Exploring the potential reasons behind liverwort community patterns has been a matter of multiplied interest for ecologists. In the present study, we recorded the liverwort taxa of Sygera Mountain growing on decaying wood, trees, soil, and rocks along an elevational gradient from 3100 m to 4500 m using complex field surveys in 2017 and 2019; we investigated the effects of elevation and various climatic factors on the liverworts’ diversity and community composition. Furthermore, we used mixed effect modeling, NMDS, ANOSIM, and CCA to help us critically assess liverwort diversity with respect to environmental variables. The results of the study showed a bimodal variation in the richness of liverwort communities according to elevation, with peaks occurring at 3500 m and 4100 m, respectively. The variation in elevation was significant, with communities at 4300 m being associated with high mean diurnal range environments and those at 3100 m and 3300 m favoring areas of higher solar radiation and the precipitation of the wettest month. Among the climatic factors, the variation in the mean diurnal range was found to be the determinant of liverwort communities. The results suggest that the mean diurnal range plays a crucial role in the distribution and community structure formation of mountain liverwort. This study deepens our understanding of liverwort ecology and emphasizes the importance of climatic variables in determining liverwort community composition.
Use of Non-Saccharomyces Yeast to Enhance the Acidity of Wines Produced in a Warm Climate Region: Effect on Wine Composition
Authors: Sánchez-Suárez Fernando , Peinado Rafael A.
Published: December 2023

One of the most notable effects of climate change, especially in warm regions, is the decrease in acidity (i.e., increase in pH) of wines and a reduction in their aromatic profile. To address this issue, must from a white grape variety with low acidity were inoculated with two non-Saccharomyces yeasts (Lachancea thermotolerans and Torulaspora delbrueckii) to enhance the acidity of the resulting wines. Basic oenological variables and major volatile compounds and polyols of the wines were analyzed, and the results were compared with those obtained through a Saccharomyces cerevisiae strain. Through multiple regression analysis, we found relations between the production of lactic acid to compounds involved in yeast metabolism and redox balance, including glycerol, acetic acid, isobutanol, isoamyl alcohols, and 2-phenylethanol. By means of principal component analysis, we obtained three components that explain more than 89% of the observed variability. The first component differentiates wines produced by L. thermotolerans; the second differentiates wines obtained by S. cerevisiae from those obtained by T. delbrueckii; and the third component is related to the temperature of fermentation. Organoleptic wines produced with S. cerevisiae were the best valuated, but taste was a highlight of the wines produced with L. thermotolerans due to possessing the best acidity.
TDLearning: Trusted Distributed Collaborative Learning Based on Blockchain Smart Contracts
Authors: Liu Jing , Hai Xuesong , Li Keqin
Published: December 2023

Massive amounts of data drive the performance of deep learning models, but in practice, data resources are often highly dispersed and bound by data privacy and security concerns, making it difficult for multiple data sources to share their local data directly. Data resources are difficult to aggregate effectively, resulting in a lack of support for model training. How to collaborate between data sources in order to aggregate the value of data resources is therefore an important research question. However, existing distributed-collaborative-learning architectures still face serious challenges in collaborating between nodes that lack mutual trust, with security and trust issues seriously affecting the confidence and willingness of data sources to participate in collaboration. Blockchain technology provides trusted distributed storage and computing, and combining it with collaboration between data sources to build trusted distributed-collaborative-learning architectures is an extremely valuable research direction for application. We propose a trusted distributed-collaborative-learning mechanism based on blockchain smart contracts. Firstly, the mechanism uses blockchain smart contracts to define and encapsulate collaborative behaviours, relationships and norms between distributed collaborative nodes. Secondly, we propose a model-fusion method based on feature fusion, which replaces the direct sharing of local data resources with distributed-model collaborative training and organises distributed data resources for distributed collaboration to improve model performance. Finally, in order to verify the trustworthiness and usability of the proposed mechanism, on the one hand, we implement formal modelling and verification of the smart contract by using Coloured Petri Net and prove that the mechanism satisfies the expected trustworthiness properties by verifying the formal model of the smart contract associated with the mechanism. On the other hand, the model-fusion method based on feature fusion is evaluated in different datasets and collaboration scenarios, while a typical collaborative-learning case is implemented for a comprehensive analysis and validation of the mechanism. The experimental results show that the proposed mechanism can provide a trusted and fair collaboration infrastructure for distributed-collaboration nodes that lack mutual trust and organise decentralised data resources for collaborative model training to develop effective global models.
Pulp Particle Classification Based on Optical Fiber Analysis and Machine Learning Techniques
Authors: Lindström Stefan B. , Amjad Rabab , Gåhlin Elin , Andersson Linn , Kaarto Marcus , Liubytska Kateryna , Persson Johan , Berg Jan-Erik , Engberg Birgitta A. , Nilsson Fritjof
Published: December 2023

In the pulp and paper industry, pulp testing is typically a labor-intensive process performed on hand-made laboratory sheets. Online quality control by automated image analysis and machine learning (ML) could provide a consistent, fast and cost-efficient alternative. In this study, four different supervised ML techniques—Lasso regression, support vector machine (SVM), feed-forward neural networks (FFNN), and recurrent neural networks (RNN)—were applied to fiber data obtained from fiber suspension micrographs analyzed by two separate image analysis software. With the built-in software of a commercial fiber analyzer optimized for speed, the maximum accuracy of 81% was achieved using the FFNN algorithm with Yeo–Johnson preprocessing. With an in-house algorithm adapted for ML by an extended set of particle attributes, a maximum accuracy of 96% was achieved with Lasso regression. A parameter capturing the average intensity of the particle in the micrograph, only available from the latter software, has a particularly strong predictive capability. The high accuracy and sensitivity of the ML results indicate that such a strategy could be very useful for quality control of fiber dispersions.
The Study of Hydrogen Volume Fraction Effects on the Flame Temperature of Turbulence Diffusion Propane Jet Flames
Authors: Yan Bingchuan , Sun Chao , Feng Qingshan , Chen Jian , Gao Yuke , Tao Changfa
Published: December 2023

This paper studies the influence of hydrogen volume fraction effects on the temperature distribution of diffusion turbulent propane jet flames. Numbers of experimental scenarios have been carried out to investigate the evolution of temperature distribution under different hydrogen volume fractions. In the continuous region, these experimental results show that the temperature distribution and the maximum temperature of diffusion of turbulent jet flames are proportional to the hydrogen volume fraction under the same heat release rate of propane. Considering the model of virtual point source and the three-stage model, the theoretical model between the hydrogen volume fraction and flame temperature has been analyzed. The relationship among the temperature distribution, hydrogen volume fraction, and heat release rate has been modified. It can provide some important references for the fire risk assessment of turbulent diffusion jet flames.
Modeling the Monthly Distribution of MODIS Active Fire Detections from a Satellite-Derived Fuel Dryness Index by Vegetation Type and Ecoregion in Mexico
Authors: Vega-Nieva Daniel José , Nava-Miranda María Guadalupe , Briseño-Reyes Jaime , López-Serrano Pablito Marcelo , Corral-Rivas José Javier , Cruz-López María Isabel , Cuahutle Martin , Ressl Rainer , Alvarado-Celestino Ernesto , Burgan Robert E.
Published: December 2023

The knowledge of the effects of fuel dryness on fire occurrence is critical for sound forest fire management planning, particularly in a changing climate. This study aimed to analyze the monthly distributions of MODIS active fire (AF) detections and their relationships with a fuel dryness index (FDI) based on satellite-derived weather and vegetation greenness. Monthly AF distributions showed unimodal distributions against FDI, which were described using generalized Weibull equations, fitting a total of 19 vegetation types and ecoregions analyzed in Mexico. Monthly peaks of fire activity occurred at lower FDI values (wetter fuels) in more hygrophytic ecosystems and ecoregions, such as wet tropical forests, compared to higher fire activity in higher FDI values (drier fuels) for the more arid ecosystems, such as desert shrublands. In addition, the range of fuel dryness at which most monthly fire activity occurred was wider for wetter vegetation types and regions compared to a narrower range of fuel dryness for higher monthly fire occurrence in the more arid vegetation types and ecoregions. The results from the current study contribute towards improving our understanding of the relationships between fuel dryness and fire occurrence in a variety of vegetation types and regions in Mexico.
The Influence of Two-Dimensional Temperature Modulation on Floating Droplet Dynamics
Authors: Nepomnyashchy Alexander , Simanovskii Ilya
Published: December 2023

We investigate the dynamics and instabilities of a droplet that floats on a liquid substrate. The substrate is cooled from below. In the framework of the slender droplet approximation and the precursor model, the problem is studied numerically. Oscillatory and stationary regimes of thermocapillary convection have been observed. The influence of a two-dimensional spatial inhomogeneity of temperature on the droplet dynamics is investigated. The two-dimensional spatial temperature inhomogeneity can suppress oscillations, changing the droplet’s shape. In a definite region of parameters, the two-dimensional spatial modulation can lead to the excitation of periodic oscillations. The influence of the Biot number on the shape of the droplets is studied.
Development of Eco-Friendly Biocomposite Films Based on Opuntia ficus-indica Cladodes Powder Blended with Gum Arabic and Xanthan Envisaging Food Packaging Applications
Authors: Oudir Malha , Ait Mesbah Zohra , Lerari Djahida , Issad Nadia , Djenane Djamel
Published: December 2023

Currently, food packaging is facing a critical transition period and a major challenge: it must preserve the food products’ quality and, at the same time, it must meet the current requirements of the circular economy and the fundamental principles of packaging materials eco-design. Our research presents the development of eco-friendly packaging films based on Opuntia ficus-indica cladodes (OFIC) as renewable resources. OFIC powder (OFICP)-agar, OFICP–agar-gum arabic (GA), and OFICP–agar-xanthan (XG) blend films were eco-friendlily prepared by a solution casting method. The films’ properties were investigated by scanning electron microscope (SEM), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (X-RD), and differential scanning calorimeter (DSC). Water solubility and moisture content were also determined. Morphology, thickness, molecular interactions, miscibility, crystallinity, and thermal properties, were affected by adjusting the gums (GA and XG) content and glycerol in the blend films. Moisture content increased with increasing glycerol and XG content, and when 1.5 g of GA was added. Water solubility decreased when glycerol was added at 50% and increased with increasing GA and XG content. FTIR and XRD confirmed strong intermolecular interactions between the different blend film compounds, which were reflected in the shifting, appearance, and disappearance of FTIR bands and XRD peaks, indicating excellent miscibility. DSC results revealed a glass transition temperature (Tg) below room temperature for all prepared blend films, indicating that they are flexible and soft at room temperature. The results corroborated that the addition of glycerol at 30% and the GA to the OFICP increased the stability of the film, making it ideal for different food packaging applications.
Unveiling the Potent Antiviral and Antioxidant Activities of an Aqueous Extract from Caesalpinia mimosoides Lamk: Cheminformatics and Molecular Docking Approaches
Authors: Klamrak Anuwatchakij , Nabnueangsap Jaran , Narkpuk Jaraspim , Saengkun Yutthakan , Janpan Piyapon , Nopkuesuk Napapuch , Chaveerach Arunrat , Teeravechyan Samaporn , Rahman Shaikh Shahinur , Dobutr Theerawat , Sitthiwong Poramet , Maraming Pornsuda , Nualkaew Natsajee , Jangpromma Nisachon , Patramanon Rina , Daduang Sakda , Daduang Jureerut
Published: December 2023

Our group previously demonstrated that Caesalpinia mimosoides Lamk exhibits many profound biological properties, including anticancer, antibacterial, and antioxidant activities. However, its antiviral activity has not yet been investigated. Here, the aqueous extract of C. mimosoides was prepared from the aerial parts (leaves, stalks, and trunks) to see whether it exerts anti-influenza (H1N1) effects and to reduce the organic solvents consumed during extraction, making it a desirable approach for the large-scale production for medical uses. Our plant extract was quantified to contain 7 g of gallic acid (GA) per 100 g of a dry sample, as determined using HPLC analysis. It also exerts potent antioxidant activities comparable to those of authentic GA. According to untargeted metabolomics (UPLC-ESI(-)-QTOF-MS/MS) with the aid of cheminformatics tools (MetFrag (version 2.1), SIRIUS (version 5.8.3), CSI:FingerID (version 4.8), and CANOPUS), the major metabolite was best annotated as “gallic acid”, phenolics (e.g., quinic acid, shikimic acid, and protocatechuic acid), sugar derivatives, and dicarboxylic acids were deduced from this plant species for the first time. The aqueous plant extract efficiently inhibited an influenza A (H1N1) virus infection of MDCK cells with an IC50 of 5.14 µg/mL. Of equal importance, hemolytic activity was absent for this plant extract, signifying its applicability as a safe antiviral agent. Molecular docking suggested that GA interacts with conserved residues (e.g., Arg152 and Asp151) located in the catalytic inner shell of the viral neuraminidase (NA), sharing the same pocket as those of anti-neuraminidase drugs, such as laninamivir and oseltamivir. Additionally, other metabolites were also found to potentially interact with the active site and the hydrophobic 430-cavity of the viral surface protein, suggesting a possibly synergistic effect of various phytochemicals. Therefore, the C. mimosoides aqueous extract may be a good candidate for coping with increasing influenza virus resistance to existing antivirals.
Exploring the Nutritional Potential of Microalgae in the Formulation of Bakery Products
Authors: Hernández-López Israel , Abadias Maribel , Prieto-Santiago Virginia , Chic-Blanco Ángela , Ortiz-Solà Jordi , Aguiló-Aguayo Ingrid
Published: December 2023

Microalgae have positioned themselves as an innovative and sustainable source of bioactive compounds and high nutritional value. The selection of a suitable food carrier is important to ease its consumption, and to preserve bioactivity through food processing. The aim of this study was to assess the suitability of different microalgae in baked products. Crackers and grissini were produced following a specific formulation, with percentages ranging from 1.5 to 3.5% of flour substituted with Spirulina, Chlorella, and Tetraselmis dry biomass in the formulas. Physico-chemical, nutritional, and sensorial characterization was carried out. The incorporation of microalgae led to increased nutritional values, including antioxidant capacity (AOX), total phenolic content (TPC) and protein content with an amino acids’ identification and quantification. Grissini with Chlorella at 3.5% and crackers with Spirulina at 1.5% levels, showed a higher overall acceptance within the panelists. For amino acid content, Spirulina crackers were shown to be rich in alanine, aspartate, and tryptophan, while Chlorella grissini stood out for being particularly rich in isoleucine, leucine, lysine, and valine. Thus, Spirulina and Chlorella could be a sustainable ingredient to formulate baked goods with an enhanced nutrimental matrix without altering their acceptability to consumers.
Disentangling the Tissue-Specific Variations of Volatile Flavor Profiles of the Lentinula edodes Fruiting Body
Authors: Guo Yuan , Zhao Jing , Wei Huixian , Gao Qi , Song Shuang , Fan Yangyang , Yan Dong , Liu Yu , Wang Shouxian
Published: December 2023

For Lentinula edodes, its characteristic flavor is the key determinant for consumer preferences. However, the tissue-specific volatile flavor variations of the fruiting body have been overlooked. Here, we comprehensively investigated the volatile flavor profiles of different tissues, including the pileus skin, context, gill, and stipe of the fruiting body, of two widely cultivated L. edodes strains (T2 and 0912) using the gas chromatography–mass spectrometry (GC–MS) technique combined with a multivariate analysis. We show that the eight-carbon and sulfur compounds, which represented 43.2–78.0% and 1.4–42.9% of the total volatile emissions for strains 0912 and T2, respectively, dominated their volatile profiles. Compared with strain T2, strain 0912 had a higher total content of eight-carbon compounds but a lower total content of sulfur compounds in the fruiting body. The sulfur compounds represented 32.2% and 42.9% of the total volatile emissions for strains 0912 and T2, respectively. In contrast, they constituted only 1.4% in the stipes of strain 0912 and 9.0% in the skin of strain T2. The proportions of the predominant C8 compounds (1-octen-3-one, 1-octen-3-ol, and 3-octanone) and sulfur compounds (lenthionine, 1,2,4-trithiolane, dimethyl disulfide, and dimethyl trisulfide) changed depending on the tissues and strains. Using machine learning, we show that the prediction accuracy for different strains and tissues using their volatile profiles could reach 100% based on the highly diverse strain- and tissue-derived volatile variations. Our results reveal and highlight for the first time the comprehensive tissue-specific volatile flavor variations of the L. edodes fruiting body. These findings underscore the significance of considering strain and tissue differences as pivotal variables when aiming to develop products with volatile flavor characteristics.
Postbiotics: Functional Food Materials and Therapeutic Agents for Cancer, Diabetes, and Inflammatory Diseases
Authors: Gurunathan Sangiliyandi , Thangaraj Pratheep , Kim Jin-Hoi
Published: December 2023

Postbiotics are (i) “soluble factors secreted by live bacteria, or released after bacterial lysis, such as enzymes, peptides, teichoic acids, peptidoglycan-derived muropeptides, polysaccharides, cell-surface proteins and organic acids”; (ii) “non-viable metabolites produced by microorganisms that exert biological effects on the hosts”; and (iii) “compounds produced by microorganisms, released from food components or microbial constituents, including non-viable cells that, when administered in adequate amounts, promote health and wellbeing”. A probiotic- and prebiotic-rich diet ensures an adequate supply of these vital nutrients. During the anaerobic fermentation of organic nutrients, such as prebiotics, postbiotics act as a benevolent bioactive molecule matrix. Postbiotics can be used as functional components in the food industry by offering a number of advantages, such as being added to foods that are harmful to probiotic survival. Postbiotic supplements have grown in popularity in the food, cosmetic, and healthcare industries because of their numerous health advantages. Their classification depends on various factors, including the type of microorganism, structural composition, and physiological functions. This review offers a succinct introduction to postbiotics while discussing their salient features and classification, production, purification, characterization, biological functions, and applications in the food industry. Furthermore, their therapeutic mechanisms as antibacterial, antiviral, antioxidant, anticancer, anti-diabetic, and anti-inflammatory agents are elucidated.
Improvement on Forecasting of Propagation of the COVID-19 Pandemic through Combining Oscillations in ARIMA Models
Authors: Hwang Eunju
Published: December 2023

Daily data on COVID-19 infections and deaths tend to possess weekly oscillations. The purpose of this work is to forecast COVID-19 data with partially cyclical fluctuations. A partially periodic oscillating ARIMA model is suggested to enhance the predictive performance. The model, optimized for improved prediction, characterizes and forecasts COVID-19 time series data marked by weekly oscillations. Parameter estimation and out-of-sample forecasting are carried out with data on daily COVID-19 infections and deaths between January 2021 and October 2022 in the USA, Germany, and Brazil, in which the COVID-19 data exhibit the strongest weekly cycle behaviors. Prediction accuracy measures, such as RMSE, MAE, and HMAE, are evaluated, and 95% prediction intervals are constructed. It was found that predictions of daily COVID-19 data can be improved considerably: a maximum of 55–65% in RMSE, 58–70% in MAE, and 46–60% in HMAE, compared to the existing models. This study provides a useful predictive model for the COVID-19 pandemic, and can help institutions manage their healthcare systems with more accurate statistical information.
The Potential Impact of a High-Frequency Telecommunication Network on Cognitive Functions: A Review
Authors: Ratul Rashed Hasan , Tasnim Maliha , Wang Hwang-Cheng , Badhon Rashadul Hasan , Kawser Mohammad Tawhid
Published: December 2023

The latest cellular technology, known as 5G-NR, is intended to significantly speed up and improve the effectiveness of wireless systems. A revolution in the telecom industry has been sparked by the widespread use of and increased reliance on cellular communication technology. Moreover, 5G and B5G technologies are expected to utilize an even higher-frequency range to achieve faster data transmission and lower latency communication. Consequently, while transmitting signals across various types of equipment and infrastructure, the general public is exposed to much higher frequencies of electromagnetic radiation. The increasing need for 5G NR base stations (gNodeB) has heightened public anxiety over potential negative health impacts. This study reviews recent research on the effects of electromagnetic waves on humans, particularly focusing on how these effects influence cognitive functions. Most research to date has not found significant differences in cognitive performance due to ubiquitous mobile communications. However, current research has largely been limited to 4G technologies, and the health effects of exposure to 5G user equipment (UE) and base stations in higher-frequency bands remain unexplored. If subsequent research suggests that exposure to high-frequency wireless networks significantly impacts cognitive functions, the deployment and acceptance of these technologies may face challenges and constraints. Therefore, such investigations are crucial for determining whether next-generation technologies pose no risk to individuals.
UV-Crosslinked Poly(N-isopropylacrylamide) Interpenetrated into Chitosan Structure with Enhancement of Mechanical Properties Implemented as Anti-Fouling Materials
Authors: Dueramae Isala , Tanaka Fumihiko , Shinyashiki Naoki , Yagihara Shin , Kita Rio
Published: December 2023

High-performance properties of interpenetration polymer network (IPN) hydrogels, based on physically crosslinked chitosan (CS) and chemically crosslinked poly(N-isopropylacrylamide) (PNiPAM), were successfully developed. The IPN of CS/PNiPAM is proposed to overcome the limited mechanical properties of the single CS network. In this study, the viscoelastic behaviors of prepared materials in both solution and gel states were extensively examined, considering the UV exposure time and crosslinker concentration as key factors. The effect of these factors on gel formation, hydrogel structures, thermal stabilities of networks, and HeLa cell adhesion were studied sequentially. The sol–gel transition was effectively demonstrated through the scaling law, which agrees well with Winter and Chambon’s theory. By subjecting the CS hydrogel to the process operation in an ethanol solution, its properties can be significantly enhanced with increased crosslinker concentration, including the shear modulus, crosslinking degree, gel strength, and thermal stability in its swollen state. The IPN samples exhibit a smooth and dense surface with irregular pores, allowing for much water absorption. The HeLa cells were adhered to and killed using the CS surface cationic charges and then released through hydrolysis by utilizing the hydrophilic/hydrophobic switchable property or thermo-reversible gelation of the PNiPAM network. The results demonstrated that IPN is a highly attractive candidate for anti-fouling materials.
Preparation and Characterization of Boza Enriched with Nonfat Dry Milk and Its Impact on the Fermentation Process
Authors: Pulatsu Ezgi , Malik Sargun , Lin Mengshi , Krishnaswamy Kiruba , Vardhanabhuti Bongkosh
Published: December 2023

Boza is an indigenous, traditional, low-alcohol and highly viscous beverage prepared by fermenting cereals. Its thick and gel-like consistency make it suitable for consumption via spoon. Although boza is a nutritious beverage, its protein content is very low (<2%). A new type of boza was developed by incorporating nonfat dry milk (NFDM) to elevate the protein content of the beverage. Different NFDM amounts (10 to 40% w/v) were added to determine the best concentration and fermentation time based on the refractive index and pH values at room temperature (0–48 h). The best sample was further characterized by rheological analyses and Fourier transform infrared (FTIR) spectroscopy. The sample with 10% NFDM was the best, as fermentation was successfully performed, and further addition of NFDM increased the initial pH. The refractive index and pH decreased from 21.9 ± 0.1 to 11.8 ± 0.1 and 5.77± 0.50 to 4.09 ± 0.35 during fermentation, respectively. The samples exhibited shear-thinning, solid-like behavior, and a gel-like structure. FTIR analysis by independent modeling of class analogy (SIMCA) demonstrated that unfermented slurry and the fermented product could be effectively differentiated. With the addition of 10% NFDM, the increase in the protein content of the boza medium became significant.
Specific Patterns in Correlations of Super-Short Tandem Repeats (SSTRs) with G+C Content, Genic and Intergenic Regions, and Retrotransposons on All Human Chromosomes
Authors: Henn Lukas , Sievers Aaron , Hausmann Michael , Hildenbrand Georg
Published: December 2023

The specific characteristics of k-mer words (2 ≤ k ≤ 11) regarding genomic distribution and evolutionary conservation were recently found. Among them are, in high abundance, words with a tandem repeat structure (repeat unit length of 1 bp to 3 bp). Furthermore, there seems to be a class of extremely short tandem repeats (≤12 bp), so far overlooked, that are non-random-distributed and, therefore, may play a crucial role in the functioning of the genome. In the following article, the positional distributions of these motifs we call super-short tandem repeats (SSTRs) were compared to other functional elements, like genes and retrotransposons. We found length- and sequence-dependent correlations between the local SSTR density and G+C content, and also between the density of SSTRs and genes, as well as correlations with retrotransposon density. In addition to many general interesting relations, we found that SINE Alu has a strong influence on the local SSTR density. Moreover, the observed connection of SSTR patterns to pseudogenes and -exons might imply a special role of SSTRs in gene expression. In summary, our findings support the idea of a special role and the functional relevance of SSTRs in the genome.
Evaluating Land Surface Temperature Trends and Explanatory Variables in the Miami Metropolitan Area from 2002–2021
Authors: Shapiro Alanna D. , Liu Weibo
Published: December 2023

Physical and climatic variables such as Tree Canopy coverage, Normalized Difference Vegetation Index (NDVI), Distance to Roads, Distance to the Coast, Impervious Surface, and Precipitation can affect land surface temperature (LST). This paper examines the relationships using linear regression models and explores LST trends in the Miami Statistical Area (MSA) between 2002 and 2021. This study evaluates the effect of dry and wet seasons as well as day and night data on LST. A multiscale investigation is used to examine LST trends at the MSA scale, the individual county level, and at the pixel level to provide a detailed local perspective. The multiscale results are needed to understand spatiotemporal LST distributions to plan mitigation measures such as planting trees or greenery to regulate temperature and reduce the impacts of surface urban heat islands. The results indicate that LST values are rising in the MSA with a positive trend throughout the 20-year study period. The rate of change (RoC) for the wet season is smaller than for the dry season. The pixel-level analysis suggests that the RoC is primarily in rural areas and less apparent in urban areas. New development in rural areas may trigger increased RoC. This RoC relates to LST in the MSA and is different from global or regional RoC using air temperature. Results also suggest that climatic explanatory variables have different impacts during the night than they do in the daytime. For instance, the Tree Canopy variable has a positive coefficient, while during the day, the Tree Canopy variable has a negative relationship with LST. The Distance to the Coast variable changes from day to night as well. The increased granularity achieved with the multiscale analysis provides critical information needed to improve the effectiveness of potential mitigation efforts.
Perceptions of Patients, Caregivers, and Healthcare Professionals toward Telemedicine Use for Cognitive and Movement Disorders in the Aegean Islands, Greece: A Pilot Study of the SI4CARE European Project
Authors: Angelopoulou Efthalia , Kontaxopoulou Dionysia , Fragkiadaki Stella , Stanitsa Evangelia , Pavlou Dimosthenis , Papatriantafyllou John , Koros Christos , Dimovski Vlado , Šemrov Darja , Papageorgiou Sokratis G.
Published: December 2023

Background: Patients with neurodegenerative diseases who live in remote areas often have limited access to specialized healthcare, and telemedicine represents a useful solution. The aim of this study was to investigate the perceptions toward the use of a specialized-tertiary telemedicine service of patients with cognitive and movement disorders, caregivers, and local healthcare professionals (HPs) in the Aegean Islands. Methods: Data were derived from the “Specialized Outpatient Clinic of Memory, Dementia and Parkinson’s disease through the National Telemedicine Network”, March 2021–March 2023. The survey included 10 questions (5-point Likert scale). Results: We received 64 questionnaires (25 patients, 18 caregivers, 21 HPs). Most participants positively perceived all aspects of telemedicine, including comfort (mean ± standard deviation: patients 4.5 ± 0.9, caregivers: 4.8 ± 0.5, HPs: 4.6 ± 0.7), access to specialized care (4.7 ± 0.6, 4.7 ± 0.5, 4.9 ± 0.4), number of transportations (4.6 ± 0.8, 4.6 ± 0.9, 4.8 ± 0.5), adequacy of follow-up (4.6 ± 0.7, 4.4 ± 0.8, 4.2 ± 0.7), future telemedicine selection (4.8 ± 0.4, 4.8 ± 0.4, 4.6 ± 0.6), perceived reliable medical assessment (4.7 ± 0.5, 4.6 ± 0.6, 4.3 ± 0.6), information delivery (4.7 ± 0.6, 4.6 ± 0.5, 4.4 ± 0.9), health status improvement (4.6 ± 0.7, 4.6 ± 0.6, 4.0 ± 0.7), cost (4.6 ± 1, 4.6 ± 1, 5.0 ± 0.2), and general satisfaction (4.8 ± 0.4, 4.7 ± 0.5, 4.5 ± 0.6). The commonest recommendations were more frequent visits, medical specialties, and dissemination of information. Conclusions: The positive perception of participants highlights the value of telemedicine for specialized healthcare for neurodegenerative disorders, especially in remote areas.