bluuebunny/crossref_metadata_2025 huggingface dataset:
Physics-Informed Neural Network Solution of Point Kinetics Equations for a Nuclear Reactor Digital Twin
Authors: Prantikos Konstantinos , Tsoukalas Lefteri H. , Heifetz Alexander
Published: October 2022

A digital twin (DT) for nuclear reactor monitoring can be implemented using either a differential equations-based physics model or a data-driven machine learning model. The challenge of a physics-model-based DT consists of achieving sufficient model fidelity to represent a complex experimental system, whereas the challenge of a data-driven DT consists of extensive training requirements and a potential lack of predictive ability. We investigate the performance of a hybrid approach, which is based on physics-informed neural networks (PINNs) that encode fundamental physical laws into the loss function of the neural network. We develop a PINN model to solve the point kinetic equations (PKEs), which are time-dependent, stiff, nonlinear, ordinary differential equations that constitute a nuclear reactor reduced-order model under the approximation of ignoring spatial dependence of the neutron flux. The PINN model solution of PKEs is developed to monitor the start-up transient of Purdue University Reactor Number One (PUR-1) using experimental parameters for the reactivity feedback schedule and the neutron source. The results demonstrate strong agreement between the PINN solution and finite difference numerical solution of PKEs. We investigate PINNs performance in both data interpolation and extrapolation. For the test cases considered, the extrapolation errors are comparable to those of interpolation predictions. Extrapolation accuracy decreases with increasing time interval.
Model NOx, SO2 Emissions Concentration and Thermal Efficiency of CFBB Based on a Hyper-Parameter Self-Optimized Broad Learning System
Authors: Ma Yunpeng , Xu Chenheng , Wang Hua , Wang Ran , Liu Shilin , Gu Xiaoying
Published: October 2022

At present, establishing a multidimensional characteristic model of a boiler combustion system plays an important role in realizing its dynamic optimization and real-time control, so as to achieve the purpose of reducing environmental pollution and saving coal resources. However, the complexity of the boiler combustion process makes it difficult to model it using traditional mathematical methods. In this paper, a kind of hyper-parameter self-optimized broad learning system by a sparrow search algorithm is proposed to model the NOx, SO2 emissions concentration and thermal efficiency of a circulation fluidized bed boiler (CFBB). A broad learning system (BLS) is a novel neural network algorithm, which shows good performance in multidimensional feature learning. However, the BLS has several hyper-parameters to be set in a wide range, so that the optimal combination between hyper-parameters is difficult to determine. This paper uses a sparrow search algorithm (SSA) to select the optimal hyper-parameters combination of the broad learning system, namely as SSA-BLS. To verify the effectiveness of SSA-BLS, ten benchmark regression datasets are applied. Experimental results show that SSA-BLS obtains good regression accuracy and model stability. Additionally, the proposed SSA-BLS is applied to model the combustion process parameters of a 330 MW circulating fluidized bed boiler. Experimental results reveal that SSA-BLS can establish the accurate prediction models for thermal efficiency, NOx emission concentration and SO2 emission concentration, separately. Altogether, SSA-BLS is an effective modelling method.
Eliminate Time Dispersion of Seismic Wavefield Simulation with Semi-Supervised Deep Learning
Authors: Han Yang , Wu Bo , Yao Gang , Ma Xiao , Wu Di
Published: October 2022

Finite-difference methods are the most widely used methods for seismic wavefield simulation. However, numerical dispersion is the main issue hindering accurate simulation. In the case where the finite-difference scheme is known, the time dispersion can be predicted mathematically and, thus, can be eliminated. However, when only pre-compiled software is available for wavefield simulation, which is common in practical applications, the software-used algorithm becomes a black box (unknown). Therefore, it is challenging to obtain the mathematical expression of the time dispersion, resulting in difficulty in eliminating the time dispersion. To solve this problem, we propose to use deep learning methods to eliminate time dispersion. We design a semi-supervised framework based on convolutional and recurrent neural networks for eliminating time dispersion caused by seismic wave modeling. The framework of our proposed neural network includes two main modules: Inverse Model and Forward Model, both of which have learnable parameters. The Inverse Model is used for eliminating time dispersion while the Forward Model is used for regularizing the training. Particularly, this framework includes two steps: Firstly, using the compiled modeling software to generate two data sets with large and small time steps. Secondly, we train these two modules for transformation between large time-step data (with time dispersion) and small time-step data (without time dispersion) by labeled and unlabeled data sets. In this work, the labeled data set is a paired data set with large time-step data and their corresponding small time-step data; the unlabeled data set is the large time-step data that need time-dispersion elimination. We use the unlabeled data set to guide the network. In this learning framework, re-training is required whenever the modeling algorithms, time interval, or frequency band is changed. Hence, we propose a transfer learning training method to extend from the trained model to another model, which reduces the computational cost caused by re-training. This minor drawback is offset overwhelmingly by the modeling efficiency gain with large time steps in large-scale production. Tests on two models confirm the effectiveness of the proposed method.
Reference Test Method for Calculating the Thermal Effect of Coal Spontaneous Combustion
Authors: Liu Wenyong , Zhang Wenzhao , Ma Shuai , Zhang Ze
Published: October 2022

During a heating experiment, there are two sources of heat that increase the temperature of a coal sample: the heat released by the oxidation reaction of the coal itself, and the heat provided by the experimental system. Here, we propose a method for measuring the thermal effect of oxidation and self-ignition through a reference experiment conducted with a material that is physically similar to coal but does not combust. The reference material used was an aggregate of alumina, fly ash, and concrete, and experiments were conducted on both materials simultaneously. The temperature of the coal sample was obtained under self-heating conditions, and compared with that of the non-combusting material. The relationship of temperature as a function of time for both materials was determined from the data, the comparison of which allowed for the thermal effect of oxidation and coal spontaneous combustion (CSC) to be calculated. The reliability of the thermal effect data obtained by the experiment was verified by chemical bond energy estimation. These results provide theoretical guidance for on-site fire prevention and extinguishing in coal mines, and are important for the further development of the understanding of CSC.
PLK-1 Interacting Checkpoint Helicase, PICH, Mediates Cellular Oxidative Stress Response
Authors: Dutta Anindita , Das Apurba , Bisht Deepa , Arya Vijendra , Muthuswami Rohini
Published: October 2022

Cells respond to oxidative stress by elevating the levels of antioxidants, signaling, and transcriptional regulation, often implemented by chromatin remodeling proteins. The study presented here shows that the expression of PICH, a Rad54-like helicase belonging to the ATP-dependent chromatin remodeling protein family, is upregulated during oxidative stress in HeLa cells. We also show that PICH regulates the expression of Nrf2, a transcription factor regulating antioxidant response in both the absence and presence of oxidative stress. The overexpression of PICH in PICH-depleted cells restored Nrf2 as well as antioxidant gene expression. In turn, Nrf2 regulated the expression of PICH in the presence of oxidative stress. ChIP experiments showed that PICH is present on the Nrf2 as well as antioxidant gene promoters, suggesting that the protein might be regulating the expression of these genes directly by binding to the DNA sequences. In addition, Nrf2 and histone acetylation (H3K27ac) also played a role in activating transcription in the presence of oxidative stress. Both Nrf2 and H3K27ac were found to be present on PICH and antioxidant promoters. Their occupancy was dependent on the PICH expression as fold enrichment was found to be decreased in PICH-depleted cells. PICH ablation led to the reduced expression of Nrf2 and impaired antioxidant response, leading to increased ROS content and thus showing PICH is essential for the cell to respond to oxidative stress.
Soil Environment and Fauna Communities in Europe after Afforestation of Post-Agricultural Lands—A Review
Authors: Malica Jacek , Urbanowski Cezary K. , Rączka Grzegorz , Skorupski Maciej , Pers-Kamczyc Emilia , Kamczyc Jacek
Published: October 2022

Afforestation can make an important contribution mitigating the effects of changing climate and provide structural and functional benefits. Afforestation also provides challenges for forest managers connected with past land-use history; therefore, there is an urgent need to summarize knowledge about such habitats and point out the gaps in knowledge for planning future studies. Although post-agricultural forests cover a large forest area in Europe, our understanding of the mechanisms governing the below-ground environment is still poor, especially when soil fauna is considered. In this study, we revised knowledge about the soil environment and the response of soil fauna to afforestation on former agricultural lands located in Europe based on research articles from the ISI Web of Science database. Data came from various but distinct locations, compared forests with different types of agricultural lands, and presented previous knowledge about soil chemistry and accompanying soil fauna communities. Finally, we selected 15 studies, investigating soil fauna communities on post-agricultural lands. The meta-analysis was based on response ratio (R) for available data, although in many cases the data were incomplete. Results indicated that post-agricultural forests differ from arable lands in reference to soil pH, but not for soil organic matter and carbon content. Different soil animal groups were represented by a similar number of studies: microfauna (seven studies) and mesofauna (nine), whereas macrofauna were represented by five studies. Meta-analysis revealed that the response of soil fauna to afforestation differed between soil fauna size classes. Additionally, in total, 18 tree species, 12 soil types, and 20 soil parameters were provided in the literature but only a few of them were presented in a single study. Future studies should include the impact of microclimate, detailed stand characteristics and soil conditions, which could help to clearly describe the impact of certain tree species growing on certain soil types. In future soil fauna ecological studies, the data should include mean values, standard deviation (SD) and/or standard effort of means (SE) for abundance, species richness, diversity indices and number of collected samples. Providing the above mentioned information will give the broad audience the opportunity to include data in future comparative analyses.
Bibliometric Analysis of the Green Gluing Technique (2000–2020): Trends and Perspectives
Authors: Rodríguez-Grau Gonzalo , Marín-Uribe Carlos , Cortés-Rodríguez Patricio , Montero Claudio , Rosales Víctor , Galarce Carlos
Published: October 2022

Wood is a sustainable and renewable material with a lower carbon footprint than other materials. However, its transformation into engineered products industrially, such as glulam, requires kiln drying, which implies energy consumption and loss of wood resources. Recent research has carried out green gluing, a variant of glulam characterized by a reduction of the drying process. Interest in it has increased as a new method of improving the use of wood that does not meet industry standards. It has been accomplished by developing adhesives for wood with high moisture content, but the variables involved are not yet completely understood. Therefore, conducting further research and analyzing the relevant publications is necessary. Bibliometric analysis was the method used, which included documents stored (from 2000 to 2020) in Scopus (Elsevier), Web of Science (Clarivate Analytics), and SciELO Citation Index (Web of Science—Clarivate Analytics) databases. The bibliometric analysis identified three main areas to develop: glue wood, glue properties, and analysis methods. The studies were concentrated on a few countries and research groups. The main progress has been made in synthetic and natural (or environmentally friendly) glue topics. The improvement of technique could enlarge the opportunities for collaboration and innovation in wood material science.
Chlorellaceae Feedstock Selection under Balanced Nutrient Limitation
Authors: Ramírez-Romero Adriana , Da Costa Magalhães Bruno , Dimitriades-Lemaire Alexandra , Sassi Jean-François , Delrue Florian , Steyer Jean-Philippe
Published: October 2022

Microalgae are an attractive source of biomass for fossil fuel alternatives and renewable energy sources. Regardless of their potential, the development of microalgal biofuels has been limited due to the associated economic and environmental costs. We followed and compared the biomass properties of six Chlorellaceae strains with a specific interest in lipid-based biofuels. The strains were cultivated under balanced nutrient limitation inducing a gradual limitation of nutrients that triggered reserve accumulation. The final biomass of each strain was characterized by its elemental and biochemical composition. Due to its high lipid content and overall composition, Chlorella vulgaris NIES 227 was identified as an ideal feedstock for biofuels with the best energy-content biomass. Its fatty acid profile also showed superior qualities for biodiesel production. Balanced nutrient limitation promoted not only the accumulation of storage compounds in all strains, but also resulted in a low content of heteroatom precursors and ashes for biofuel applications.
Fire and Herbivory Interactively Suppress the Survival and Growth of Trees in an African Semiarid Savanna
Authors: Ngugi Mary W. , Kimuyu Duncan M. , Sensenig Ryan L. , Odadi Wilfred O. , Kiboi Samuel K. , Omari Joyce K. , Young Truman P.
Published: October 2022

There has been a long-standing interest in understanding how interactions between fire and herbivory influence woody vegetation dynamics in savanna ecosystems. However, controlled, replicated experiments examining how different fire regimes interact with different herbivore groups are rare. We tested the effects of single and repeated burns, crossed with six replicated herbivore treatments, on the mortality and growth of woody vegetation in the Kenya Long-term Exclosure Experiment plots located in a semi-arid savanna system in central Kenya. Burned plots experienced higher tree mortality overall, but differences between burns and non-burns were only significant in plots excluding all wild herbivores and in plots accessible to megaherbivores. Cattle ameliorated the negative effects of repeat burns on tree mortality, perhaps by suppressing fuel load accumulation. Across all herbivore treatments, trees experienced a significant reduction in height within the first two years after fire (top-kill), which was followed by a gradual recovery. Saplings and coppices subjected to repeated burns regrew faster than those that were burned once, except in the presence of megaherbivores. This study highlights strong context-dependent interactions between fire and different herbivore groups, and extends previous approaches to understanding fire–herbivory interactions, which have tended to lump the effects of different herbivore groups, or study them separately.
An Exploration of Pepino (Solanum muricatum) Flavor Compounds Using Machine Learning Combined with Metabolomics and Sensory Evaluation
Authors: Sun Zhu , Zhao Wenwen , Li Yaping , Si Cheng , Sun Xuemei , Zhong Qiwen , Yang Shipeng
Published: October 2022

Flavor is one of the most important characteristics that directly determines the popularity of a food. Moreover, the flavor of fruits is determined by the interaction of multiple metabolic components. Pepino, an emerging horticultural crop, is popular for its unique melon-like flavor. We analyzed metabolomics data from three different pepino growing regions in Haidong, Wuwei, and Jiuquan and counted the status of sweetness, acidity, flavor, and overall liking ratings of pepino fruit in these three regions by sensory panels. The metabolomics and flavor ratings were also integrated and analyzed using statistical and machine learning models, which in turn predicted the sensory panel ratings of consumers based on the chemical composition of the fruit. The results showed that pepino fruit produced in the Jiuquan region received the highest ratings in sweetness, flavor intensity, and liking, and the results with the highest contribution based on sensory evaluation showed that nucleotides and derivatives, phenolic acids, amino acids and derivatives, saccharides, and alcohols were rated in sweetness (74.40%), acidity (51.57%), flavor (56.41%), and likability (33.73%) dominated. We employed 14 machine learning strategies trained on the discovery samples to accurately predict the outcome of sweetness, sourness, flavor, and liking in the replication samples. The Radial Sigma SVM model predicted with better accuracy than the other machine learning models. Then we used the machine learning models to determine which metabolites influenced both pepino flavor and consumer preference. A total of 27 metabolites most important for pepino flavor attributes to distinguish pepino originating from three regions were screened. Substances such as N-acetylhistamine, arginine, and caffeic acid can enhance pepino‘s flavor intensity, and metabolites such as glycerol 3-phosphate, aconitic acid, and sucrose all acted as important variables in explaining the liking preference. While glycolic acid and orthophosphate inhibit sweetness and enhance sourness, sucrose has the opposite effect. Machine learning can identify the types of metabolites that influence fruit flavor by linking metabolomics of fruit with sensory evaluation among consumers, which conduces breeders to incorporate fruit flavor as a trait earlier in the breeding process, making it possible to select and release fruit with more flavor.
Effects of Drying Methods on the Physicochemical Aspects and Volatile Compounds of Lyophyllum decastes
Authors: Yang Bin , Huang Jianhang , Jin Wensong , Sun Shujing , Hu Kaihui , Li Jiahuan
Published: October 2022

In this study, fresh Lyophyllum decastes was dried using hot air drying (HAD), hot air combined with vacuum drying (HAVD), and vacuum freeze drying (VFD). Additionally, the quality and volatile compounds were analyzed. VFD achieved the best color retention, the highest rehydration capacity, and the slightest damaged tissue structure; however, it recorded the longest drying time and the highest energy consumption. HAD was the most energy-efficient of the three methods. Furthermore, the products with more hardness and elasticity were obtained by HAD and HAVD—this finding was convenient for transportation. In addition, GC-IMS demonstrated that the flavor components had significantly changed after drying. A total of 57 volatile flavor compounds was identified, and the aldehyde, alcohol, and ketone compounds were the primary ingredient of the L. decastes flavor component, whereby the relative content of the HAD sample was apparently higher than HAVD and VFD. Taken together, VFD was better at preserving the color and shape of fresh L. decastes, but HAD was more appropriate for drying L. decastes because of the lower energy consumption, and was more economical. Meanwhile, HAD could be used to produce a more intense aroma.
Glycaemic Index of Gluten-Free Biscuits with Resistant Starch and Sucrose Replacers: An In Vivo and In Vitro Comparative Study
Authors: Di Cairano Maria , Tchuenbou-Magaia Fideline Laure , Condelli Nicola , Cela Nazarena , Ojo Constance Chizoma , Radecka Iza , Dunmore Simon , Galgano Fernanda
Published: October 2022

The glycaemic index (GI) is used to demonstrate the tendency of foods to increase blood glucose and is thus an important characteristic of newly formulated foods to tackle the rising prevalence of diabetics and associated diseases. The GI of gluten-free biscuits formulated with alternate flours, resistant starch and sucrose replacers was determined using in vivo methods with human subjects. The relationship between in vivo GI values and the predicted glycaemic index (pGI) from the in vitro digestibility-based protocols, generally used by researchers, was established. The in vivo data showed a gradual reduction in GI with increased levels of sucrose substitution by maltitol and inulin with biscuits where sucrose was fully replaced, showing the lowest GI of 33. The correlation between the GI and pGI was food formulation-dependent, even though GI values were lower than the reported pGI. Applying a correction factor to pGI tend to close the gap between the GI and pGI for some formulations but also causes an underestimation of GI for other samples. The results thus suggest that it may not be appropriate to use pGI data to classify food products according to their GI.
A Review of the Current State and Future Prospects in Resource Recovery of Chinese Cereal Vinegar Residue
Authors: Wang Ke , Yu Yongjian , Liu Shuangping , Zhu Yuanyuan , Liu Peng , Yu Zhen , Wang Yuqin
Published: October 2022

Vinegar residue (VR) is a typical organic solid waste in Chinese cereal vinegar production. It is characterized by high yield, high moisture and low pH and is rich in lignocellulose and other organic matter. To avoid the environmental pollution caused by VR, it should be properly treated. The industry’s existing treatment processes, landfills and incineration, cause secondary pollution and waste of resources. Therefore, there is an urgent demand for environmentally friendly and cost-effective resource recovery technologies for VR. To date, a considerable amount of research has been performed in the area of resource recovery technologies for VR. This review summarizes the reported resource recovery technologies, mainly anaerobic digestion, feed production, fertilizer production, high-value product production and soil/water remediation. The principles, advantages and challenges of these technologies are highlighted. Finally, as a future perspective, a cascade and full utilization model for VR is proposed by considering the inherent drawbacks and economic-environmental feasibility of these technologies.
Andean Sprouted Pseudocereals to Produce Healthier Extrudates: Impact in Nutritional and Physicochemical Properties
Authors: Paucar-Menacho Luz , Schmiele Marcio , Lavado-Cruz Alicia , Verona-Ruiz Anggie , Mollá Carmen , Peñas Elena , Frias Juana , Simpalo-Lopez Wilson , Castillo-Martínez Williams , Martínez-Villaluenga Cristina
Published: October 2022

The tailored formulation of raw materials and the combination of grain germination and extrusion processes could be a promising strategy to achieve the desired goal of developing healthier expanded extrudates without compromising sensory properties. In this study, modifications in the nutritional, bioactive profile and physicochemical properties of corn extrudates as influenced by the complete or partial replacement by sprouted quinoa (Chenopodium quinoa Willd) and cañihua (Chenopodium pallidicaule Aellen) were investigated. A simplex centroid mixture design was used to study the effects of formulation on nutritional and physicochemical properties of extrudates, and a desirability function was applied to identify the optimal ingredient ratio in flour blends to achieve desired nutritional, texture and color goals. Partial incorporation of sprouted quinoa flour (SQF) and cañihua flour (SCF) in corn grits (CG)-based extrudates increased phytic acid (PA), total soluble phenolic compounds (TSPC), γ-aminobutyric acid (GABA) and oxygen radical antioxidant activity (ORAC) of the extrudates. Sprouted grain flour usually results in an deleterious effect physicochemical properties of extrudates, but the partial mixture of CG with SQF and SCF circumvented the negative effect of germinated flours, improving technological properties, favoring the expansion index and bulk density and increasing water solubility. Two optimal formulations were identified: 0% CG, 14% SQF and 86% SCF (OPM1) and 24% CG, 17% SQF and 59% SCF (OPM2). The optimized extrudates showed a reduced amount of starch and remarkably higher content of total dietary fiber, protein, lipids, ash, PA, TSPC, GABA and ORAC as compared to those in 100% CG extrudates. During digestion, PA, TSPC, GABA and ORAC showed good stability in physiological conditions. Higher antioxidant activity and amounts of bioaccessible TSPC and GABA were found in OPM1 and OPM2 digestates as compared to those in 100% CG extrudates.
Investigation of a Nonlinear Coupled (k, ψ)–Hilfer Fractional Differential System with Coupled (k, ψ)–Riemann–Liouville Fractional Integral Boundary Conditions
Authors: Samadi Ayub , Ntouyas Sotiris K. , Ahmad Bashir , Tariboon Jessada
Published: October 2022

This paper is concerned with the existence of solutions for a new boundary value problem of nonlinear coupled (k,ψ)–Hilfer fractional differential equations subject to coupled (k,ψ)–Riemann–Liouville fractional integral boundary conditions. We prove two existence results by applying the Leray–Schauder alternative, and Krasnosel’skiĭ’s fixed-point theorem under different criteria, while the third result, concerning the uniqueness of solutions for the given problem, relies on the Banach’s contraction mapping principle. Examples are included for illustrating the abstract results.
Hydroxyl Spectroscopy of Laboratory Air Laser-Ignition
Authors: Parigger Christian G.
Published: October 2022

This work investigates spatial and temporal distributions of hydroxyl, OH, in laser-plasma in laboratory air at standard ambient temperature and pressure. Of interest are determination of temperature and density of OH and establishment of a correlation of molecular OH emission spectra with shadow graphs for time delays of 50 to 100 μs, analogous to previous work on shadow graph and emission spectroscopy correlation for cyanide, CN, in gas mixtures and for time delays of the order of 1 μs. Wavelength- and sensitivity-corrected spatiotemporal data analysis focuses on temperature inferences using molecular OH emission spectroscopy. Near-IR radiation from a Q-switched laser device initiates optical breakdown in laboratory air. The laser device provides 6 ns, up to 850 milli Joule, pulses at a wavelength of 1064 nm, and focal irradiance in the range of 1 to 10 terawatt per centimeter-squared. Frequency doubled beams are utilized for capturing shadow graphs for visualization of the breakdown kernel at time delays in the range of 0.1 to 100 μs. OH emission spectra of the laser plasma, spatially resolved along the slit dimension, are recorded in the wavelength range of 298 nm to 321 nm, and with gate widths adjusted to 10 μs for the intensified charge-coupled device that is mounted at the exit plane of a 0.64 m Czerny-Turner configuration spectrometer. Diatomic OH signals occur due to recombination of the plasma and are clearly distinguishable for time delays larger than 50 μs, but are masked by spectra of N2 early in the plasma decay.
On the Use of Agile Optimization for Efficient Energy Consumption in Smart Cities’s Transportation and Mobility
Authors: Ghorbanioskalaei Elnaz , Herrera Erika M. , Ammouriova Majsa , Juan Angel A.
Published: October 2022

Urban logistics consumes a large portion of energy resources worldwide. Thus, optimization algorithms are used to define mobility modes, vehicle fleets, routing plans, and last-mile delivery operations to reduce energy consumption such as metaheuristics. With the emergence of smart cities, new opportunities were defined, such as carsharing and ridesharing. In addition to last-mile delivery, these opportunities form a challenging problem because of the dynamism they possess. New orders or ride requests could be placed or canceled at any time. Further, transportation times might evolve due to traffic conditions. These dynamic changes challenge traditional optimization methods to propose solutions in real-time to large-scale energy-optimization problems. Thus, a more `agile optimization’ approach is required to provide fast solutions to optimization problems when these changes occur. Agile optimization combines biased randomization and parallelism. It provides `good’ solutions compared to solutions found by traditional optimization methods, such as in-team orienteering problems. Additionally, these solutions are found in short wall clock, real-time.
Thermoresponsive Cationic Polymers: PFAS Binding Performance under Variable pH, Temperature and Comonomer Composition
Authors: Frazar E. Molly , Smith Anicah , Dziubla Thomas , Hilt J. Zach
Published: October 2022

The versatility and unique qualities of thermoresponsive polymeric systems have led to the application of these materials in a multitude of fields. One such field that can significantly benefit from the use of innovative, smart materials is environmental remediation. Of particular significance, multifunctional poly(N-isopropylacrylamide) (PNIPAAm) systems based on PNIPAAm copolymerized with various cationic comonomers have the opportunity to target and attract negatively charged pollutants such as perfluorooctanoic acid (PFOA). The thermoresponsive cationic PNIPAAm systems developed in this work were functionalized with cationic monomers N-[3-(dimethylamino)propyl]acrylamide (DMAPA) and (3-acrylamidopropyl)trimethylammonium chloride (DMAPAQ). The polymers were examined for swelling capacity behavior and PFOA binding potential when exposed to aqueous environments with varying pH and temperature. Comonomer loading percentages had the most significant effect on polymer swelling behavior and temperature responsiveness as compared to aqueous pH. PFOA removal efficiency was greatly improved with the addition of DMAPA and DMAPAQ monomers. Aqueous pH and buffer selection were important factors when examining binding potential of the polymers, as buffered aqueous environments altered polymer PFOA removal quite drastically. The role of temperature on binding potential was not as expected and had no discernible effect on the ability of DMAPAQ polymers to remove PFOA. Overall, the cationic systems show interesting swelling behavior and significant PFOA removal results that can be explored further for potential environmental remediation applications.
Reference Gene Selection for qPCR Analysis in Schima superba under Abiotic Stress
Authors: Yao Jun , Zhu Gang , Liang Dongcheng , He Boxiang , Wang Yingli , Cai Yanling , Zhang Qian
Published: October 2022

Quantitative real-time PCR (qPCR) is an indispensable technique for gene expression analysis in modern molecular biology. The selection and evaluation of suitable reference genes is a prerequisite for accurate gene expression analysis. Schimasuperba is a valuable tree species that is environmentally adaptable and highly fire-resistant. In this study, 12 candidate reference genes were selected to check their stability of gene expression in different tissues under abiotic stresses: cold stress, salt stress, and drought stress by ΔCt, geNorm, NormFinder, BestKeeper, and RefFinder. The results indicated that AP-2 was the most stably expressed overall and for the cold stress and drought stress. eIF-5α gene expression was the most stable under the salt stress treatment, while UBQ expression was the most stable across mature leaves, shoots, stems, and roots. In contrast, UBC20, GAPDH, and TUB were the least stably expressed genes tested. This study delivers valid reference genes in S. superba under the different experimental conditions, providing an important resource for the subsequent elucidation of the abiotic stress adaptation mechanisms and genes with biological importance.
A Comparative Presentation of Mouse Models That Recapitulate Most Features of Alport Syndrome
Authors: Nikolaou Stavros , Deltas Constantinos
Published: October 2022

Alport syndrome is a hereditary kidney disease caused by mutations in the three genes encoding for collagen IV: COL4A3, COL4A4, and COL4A5. Several mouse models have been created for the study of this disease with variable phenotypic outcomes. This review is an up-to-date presentation of the current mouse models existing in the literature with a detailed comparison of the phenotypic features characterizing each model. Although in humans it is primarily a glomerulopathy, data suggest that in some mouse models, the initial symptoms appear in the tubule-interstitial region rather than the glomerulus. Additionally, in some other models, the severity of disease in the tubule-interstitial region is affected by the genetic background. In conclusion, the phenotypic spectrum of each model appears to be affected by the model’s genetic background, the position of the genetic alteration within the gene, and the type of the genetic alteration. Despite these disparities, mouse models recapitulate with relatively high fidelity several features of the human disease, which makes them useful for studies aimed at better understanding cellular pathomechanisms and for finding new treatments.
Land Use and Water-Quality Joint Dynamics of the Córrego da Formiga, Brazilian Cerrado Headwaters
Authors: Giongo Pedro Rogerio , Oliveira Assis Ana Paula Aparecida de , Silva Marcos Vinícius da , Montenegro Abelardo Antônio de Assunção , Taveira José Henrique da Silva , Costa Adriana Rodolfo da , Silva Patrícia Costa , Giongo Angelina Maria Marcomini , Pandorfi Héliton , Santos Alessandro José Marques , Backes Clarice , Ferreira Maria Beatriz , Silva Jhon Lennon Bezerra da
Published: October 2022

The Brazilian Cerrado biome provides relevant ecosystem services for Brazil and South America, being strategic for the planning and management of water resources as well as for agribusiness. The objective was to evaluate the water quality along the course of the Córrego da Formiga in a virgin portion of the Brazilian Cerrado, the relationship of land use with physical-chemical and biological parameters of the water, and the inflow of the tributary. Five water collection points were defined (between the source and mouth) and observed on a quarterly scale in 2015, water samples were collected and analyzed for physical-chemical and biological parameters in the laboratory, and flow measurements were performed at the same point and day of water collection. To identify and quantify land use and land cover (LULC) in the watershed, an image from the Landsat8-OLI satellite was obtained, and other geomorphological data from hypsometry (Topodata-INPE) were obtained to generate the slope, basin delimitation, and contribution area for each water collection point. The LULC percentages for each area of contribution to the water collection points were correlated with the physical-chemical and biological parameters of the water and submitted to multivariate analysis (PLS-DA) for analysis and grouping among the five analyzed points. Changes in water-quality patterns were more pronounced concerning the time when the first and last sampling was performed (rainy period) and may be influenced by the increase in the volume of water in these periods. The stream flow is highly variable over time and between points, with the lowest recorded flow being 0.1 L s−1 (P1) and the highest being 947.80 L s−1 (P5). Córrego da Formiga has class III water quality (CONAMA resolution 357), which characterizes small restrictions on the use of water for multiple uses. The soil cover with native vegetation is just over 12%, while the predominance was of the classes of sugar cane (62.42%) and pasture (19.33%). The PLS-DA analysis allowed separating the water analysis points between P1, P2, P3, and P5, while P4 was superimposed on others. It was also possible to verify that the parameters that weighed the most for this separation of water quality were pH, alkalinity_T, alkalinity_h, calcium, and hardness, all with a tendency to increase concentration from the source (P1) to the mouth (P5). As for water quality, it was also possible to verify that points P2 and P5 presented better water-quality conditions.
When the Pandemic Will Be Over: Lots of Hope and Some Concerns
Authors: Azzolino Domenico , Spolidoro Giulia Carla Immacolata , Mazzocchi Alessandra , Agostoni Carlo , Cesari Matteo
Published: October 2022

The COVID-19 pandemic significantly threatened healthcare systems worldwide. The worst-hit population has been represented by older people with underlying chronic comorbidities, while children and adolescents developed mild or asymptomatic forms of the disease. However, certain medical conditions (i.e., obesity, respiratory, or neurological or immune disorders) may increase the risk for poor health outcomes even in young and middle-aged people. Beyond the direct negative effects of the infection, the pandemic posed several health challenges through an increase in psycho–social issues (i.e., anxiety, depression, fatigue, sleep alterations, loneliness, reduced assistance, and loss of income). Accordingly, the pandemic is negatively impacting the accumulation of the functional reserves of each individual, starting from early life. With the long-term effects of the pandemic to be seen in the coming years, clinicians must be prepared to manage such high clinical complexity of people they encounter, through the implementation of multidimensional and multidisciplinary interventions.
Factors Influencing the Health-Related Quality of Life of Workers According to the Type of Work
Authors: Kim Sunae , Kwon Myoungjin , Seo Kawoun
Published: October 2022

This paper describes a descriptive cross-sectional study that was conducted to identify and compare the factors affecting health-related quality of life (HRQoL) according to the type of work. The method involved a secondary analysis of 4131 workers who participated in the first year of the 8th Korea National Health and Nutrition Examination Survey (2019). In this study, a complex sample plan file was created and then weighted and analyzed. For the analyses, frequency, χ2-test, t-test, and linear regression analyses were used for complex sample analysis. Factors that significantly affected the HRQoL of daytime workers were educational background, living with a spouse, regular work, depression for two consecutive weeks, and suicidal thoughts. The explanatory power was 18.9% (p < 0.001). The factor that significantly affected the HRQoL of shift workers was whether they took dietary supplements for 2 weeks or more during the past year, and the explanatory power was 17.6% (p = 0.007). This study confirmed that the factors affecting HRQoL differ according to the type of work. Based on the results of this study, when developing a program to improve the HRQoL of workers, it is necessary to establish a differentiated strategy according to the type of work.
Global Methylation Analysis Using MSAP Reveals Differences in Chilling-Associated DNA Methylation Changes during Dormancy Release in Contrasting Sweet Cherry Varieties
Authors: Narváez Gabriela , Muñoz-Espinoza Claudia , Soto Esteban , Rothkegel Karin , Bastías Macarena , Gutiérrez José , Bravo Soraya , Hasbún Rodrigo , Meneses Claudio , Almeida Andrea Miyasaka
Published: October 2022

Dormancy is an adaptive strategy developed by temperate perennial crops to protect overwinter tissues from unfavorable environmental conditions. Sweet cherry (Prunus avium L.), a member of the Rosaceae family, requires chilling to overcome dormancy. The time of harvest is directly correlated with chilling requirements in sweet cherries. Consequently, early and late season varieties have low and high chilling requirements, respectively. There is evidence that the expression of dormancy-related genes is regulated by DNA methylation. In this work, methylation-sensitive amplified polymorphism (MSAP) was applied to study genome-wide DNA methylation changes associated with dormancy in two low-chill varieties, ‘Royal Dawn’ and ‘Glen Red’, and one high-chill variety, ‘Kordia’. Our primary results suggest that the occurrence of progressive DNA demethylation is associated with chilling accumulation during dormancy in the three varieties, independent of their chilling requirements. Genes were identified with different methylation status changes, detected by MSAP, related to cell wall remodeling and energy metabolism. Several MSAP profiles among the varieties were observed, suggesting that fine epigenetic control is required to coordinate hormonal and environmental signals that induce dormancy and its release.
In Vitro Propagation of Pyracantha angustifolia (Franch.) C.K. Schneid.
Authors: Kaviani Behzad , Deltalab Bahareh , Kulus Dariusz , Tymoszuk Alicja , Bagheri Hamideh , Azarinejad Taha
Published: October 2022

Narrow-leaf firethorn or pyracantha (Pyracantha angustifolia (Franch.) C.K. Schneid.), from the family Rosaceae, is a species of large and thorny evergreen shrub. In this study, a procedure is presented for efficient axillary shoot multiplication and root induction in P. angustifolia using Murashige and Skoog (MS), woody plant (WPM), and Linsmaier and Skoog (LS) culture media supplanted with 6-benzylaminopurine (BAP) and indole-3-butyric acid (IBA). The disinfection of the axillary buds was performed with a 70.23% success rate on a basal MS medium augmented with 0.5 mg·L−1 gibberellic acid (GA3). Uniform and axenic explants were then cultured on MS, WPM, and LS media enriched with different concentrations of BAP, 0.3 mg·L−1 GA3, and 0.1 mg·L−1 IBA. The highest multiplication coefficient (2.389) was obtained for the MS medium supplemented with 2.5 mg·L−1 BAP. After one month, newly formed micro-shoots were transferred to rooting media (MS, WPM, and LS) containing different concentrations of IBA, together with a constant concentration of 0.1 mg·L−1 BAP. The micro-shoots were kept in the dark for one week and then cultured in a 16/8 h light/dark regime. The MS medium supplemented with 1 mg·L−1 IBA was the most effective in stimulating rooting (88.76% of micro-shoots). The highest number of roots (3.5 per micro-shoot) was produced in the MS medium enriched with 1.5 mg·L−1 IBA. The rooted plantlets were transferred into pots filled with perlite and peat moss in a 2:1 proportion and acclimatized to ambient greenhouse conditions, with a resultant mean 92.84% survival rate. Thus, this protocol can be successfully applied for the in vitro mass propagation of P. angustifolia.
Projected Effects of Climate Change on the Energy Footprints of U.S. Drinking Water Utilities
Authors: Sowby Robert B. , Hales Riley C.
Published: October 2022

Drinking water systems’ energy footprints depend mostly on the source, quality, and volume of water supply, but also on local temperature and precipitation, both of which are changing with the global climate. From a previous survey, we develop an equation for modeling relative changes in U.S. water utilities’ annual energy use, in which their energy use increases with temperature and decreases with precipitation. To demonstrate, we insert gridded projections from three scenarios in the EPA’s Climate Resilience Evaluation and Awareness Tool (CREAT) and compare 2035 and 2060 periods with a 1981–2010 baseline. Averaged over the continental United States, the 2060 central scenario projects 2.7 °C warmer temperatures and 2.9 cm more annual precipitation. For the same water demand, we estimate that these conditions will cause U.S. water systems’ energy use to change by −0.7% to 13.7% depending on the location (average 8.5% across all grid cells). Warming accounts for a general increase, and local changes in precipitation can add to or subtract from it. We present maps showing the spatial variability for each scenario. Water systems are essential infrastructure that support sustainable communities, and the analysis underscores their needs for energy management, renewable energy, water conservation, and climate change resilience.
Changes in Doctor–Patient Relationships in China during COVID-19: A Text Mining Analysis
Authors: Li Jiaxuan , Pang Patrick Cheong-Iao , Xiao Yundan , Wong Dennis
Published: October 2022

Doctor–patient relationships (DPRs) in China have been straining. With the emergence of the COVID-19 pandemic, the relationships and interactions between patients and doctors are changing. This study investigated how patients’ attitudes toward physicians changed during the pandemic and what factors were associated with these changes, leading to insights for improving management in the healthcare sector. This paper collected 58,600 comments regarding Chinese doctors from three regions from the online health platform Good Doctors Online (haodf.com, accessed on 13 October 2022). These comments were analyzed using text mining techniques, such as sentiment and word frequency analyses. The results showed improvements in DPRs after the pandemic, and the degree of improvement was related to the extent to which a location was affected. The findings also suggest that administrative services in the healthcare sector need further improvement. Based on these results, we summarize relevant recommendations at the end of this paper.
The Experiences of Informal Carers during the COVID-19 Pandemic: A Qualitative Systematic Review
Authors: Bailey Cara , Guo Ping , MacArtney John , Finucane Anne , Swan Susan , Meade Richard , Wagstaff Ellie
Published: October 2022

Objectives: To identify, critically appraise and synthesise the qualitative literature on the experiences of informal carers of people with long-term conditions during the COVID-19 pandemic. Design: A qualitative systematic literature review. Data Sources: Eight electronic databases were systematically searched (Medline, Embase, CINAHL, PubMed, PsychINFO, Web of Science, Nursing and Allied Health and ASSIA) along with Google Scholar and handsearching via secondary sources. Study selection: Eligible studies had to include the experiences of informal carers (adults who are 65 or older), use a qualitative methodology and had to be written in English. Data extraction and synthesis: Retrieved papers were quality assessed using the Critical Appraisal Skills Programme qualitative checklist and ranked for quality. Thematic analysis was used to synthesise the findings. Results: Fourteen studies were included, all from medical or nursing journals (n = 5 specifically gerontology). Four main themes were identified: (i) fear, (ii) uncertainty, (iii) burden and (iv) staying connected. Caregiving demands have increased for carers during the pandemic, as well as negative emotions such as fear and uncertainty. At the same time, less social support has been available, leading to concerns about carers’ wellbeing and ability to cope. Conclusion: Carers’ needs have been exacerbated by the COVID-19 pandemic. Greater practical and emotional support is needed for carers from both formal services and community sources that considers their changing needs and offers educational and emotional support for long-term wellbeing. Strengths and Limitations: (1) This is the first systematic review to explore in depth the experiences of informal carers caring for people with a range of long-term conditions and from an international context. (2) The review includes an analysis of the quality of the studies, as well as a study of their relative contributions. (3) Further research is needed to explore the physical, emotional and financial impact of the pandemic for bereaved carers which is not captured in this review due to the lack of empirical data available at the time of review.