bluuebunny/crossref_metadata_2025 huggingface dataset:
Inorganic Nitrogen-Containing Aerosol Deposition Caused “Excessive Photosynthesis” of Herbs, Resulting in Increased Nitrogen Demand
Authors: Ge Zhiwei , Ma Yunran , Xing Wei , Wu Yongbo , Peng Sili , Mao Lingfeng , Miao Zimei
Published: August 2022

The amount of atmospheric nitrogen-containing aerosols has increased dramatically due to the globally rising levels of nitrogen from fertilization and atmospheric deposition. Although the balance of carbon and nitrogen in plants is a crucial component of physiological and biochemical indexes and plays a key role in adaptive regulation, our understanding of how nitrogen-containing aerosols affect this remains limited; in particular, regarding the associated mechanisms. Using a fumigation particle generator, we generated ammonium nitrate solution (in four concentrations of 0, 15, 30, 60 kg N hm−2 year−1) into droplets, in 90% of which the diameters were less than 2.5 μm, in the range of 0.35–4 μm, and fumigated Iris germanica L. and Portulaca grandiflora Hook. for 30 days in April and August. We found that the weight percentage of nitrogen in the upper epidermis, mesophyll tissue, and bulk of leaves decreased significantly with the N addition rate, which caused a decrease of carbon:nitrogen ratio, due to the enhanced net photosynthetic rate. Compared with Portulaca grandiflora Hook., Iris germanica L. responded more significantly to the disturbance of N addition, resulting in a decrease in the weight percentage of nitrogen in the roots, due to a lower nitrogen use efficiency. In addition, the superoxide dismutase activity of the two plants was inhibited with a higher concentration of nitrogen sol; a reduction of superoxide dismutase activity in plants means that the resistance of plants to various environmental stresses is reduced, and this decrease in superoxide dismutase activity may be related to ROS signaling. The results suggest that inorganic nitrogen-containing aerosols caused excessive stress to plants, especially for Iris germanica L.
Chemical Profiling and Biological Activities of Pelargonium graveolens Essential Oils at Three Different Phenological Stages
Authors: Al-Mijalli Samiah Hamad , Mrabti Hanae Naceiri , Assaggaf Hamza , Attar Ammar A. , Hamed Munerah , Baaboua Aicha EL , Omari Nasreddine El , Menyiy Naoual El , Hazzoumi Zakaria , Sheikh Ryan A , Zengin Gokhan , Sut Stefania , Dall’Acqua Stefano , Bouyahya Abdelhakim
Published: August 2022

The aim of this work was the determination of Pelargonium graveolens (aerial parts) volatile compounds at three developmental stages and the evaluation of their antioxidant, antidiabetic, dermaprotective, anti-inflammatory, and antibacterial effects. The aerial parts of Pelargonium graveolens were collected at three stages, namely the vegetative, beginning, and full flowering. Pelargonium graveolens essential oils were extracted from the dried materials of these aerial parts by hydrodistillation. The volatiles were analyzed by Gas Chromatography-Mass Spectrometry GC-MS, and the antioxidant activity was assessed by DPPH, ABTS, H2O2, and FRAP assays. The in vitro antidiabetic effect was evaluated by the inhibition of α-amylase, α-glucosidase, and lipase enzymes, while the antibacterial activity was assessed against six bacterial strains using an agar well diffusion assay and a microdilution method. The main constituents were menthol, menthene, eremophilene, isoborneol, isogeraniol, α-pinene, linalyl acetate, and 3-carene, with quantitative differences at the three phenological stages. The essential oil at the full flowering stage showed the best antioxidant activity, with IC50 values of 83.26 ± 0.01, 116.42 ± 0.07, 132.25 ± 0.11, and 48.67 ± 0.04 μg/mL for DPPH, FRAP, ABTS, and H2O2 assays, respectively. This oil also exhibited significant effects against α-amylase (IC50 = 43.33 ± 0.01 μg/mL), α-glucosidase (IC50 = 19.04 ± 0.01 μg/mL), lipase (IC50 = 24.33 ± 0.05 μg/mL), 5-lipoxygenase (IC50 = 39.31 ± 0.01 μg/mL), and tyrosinase (IC50 = 124.49 ± 0.07 μg/mL). The essential oil extracted at the full flowering stage showed the best antibacterial effect against a panel of microorganisms with diameter inhibition zones ranging between 11.00 ± 0.17 mm and 17.30 ± 0.17 mm and MIC values from 0.25% to 2% v/v. Overall, the results presented here suggest that the full flowering stage is the best optimal harvest time of Pelargonium graveolens for food and pharmaceutical applications.
Seed Priming with ZnO and Fe3O4 Nanoparticles Alleviate the Lead Toxicity in Basella alba L. through Reduced Lead Uptake and Regulation of ROS
Authors: Gupta Nakul , Singh Prabhakar Mohan , Sagar Vidya , Pandya Alok , Chinnappa Manimurugan , Kumar Rajesh , Bahadur Anant
Published: August 2022

The increased lead (Pb) content in the environment has an impact on all living beings, including plant growth and quality. The present study aims to investigate the protective roles of zinc (Zn)- and iron (Fe)- nanoparticles (NPs) in alleviating stress symptoms caused by lead (Pb) exposure in Basella alba seedlings. For this purpose, 15 different treatment combinations of seed priming with two NPs at 0 and 200 mg L−1, and five Pb levels (0, 4, 8, 15, 20 mM) were chosen. Pb stress (20 mM) was found to reduce seed germination by 72.8% and seedling growth, particularly root length, by 92% when compared to the control. Under different Pb concentrations, seed priming with ZnNPs (200 mg L−1) and FeNPs (200 mg L−1) increased seed germination by 34.7% and 54.9%, respectively, and root length by 152.9% and 252.9%, respectively. In 20 mM Pb stress, NPs primed seedling showed decrease in Pb content by 33.7% with ZnNPs and 32.6% with FeNPs. Increased Pb stress resulted in increased reactive oxygen species (ROS) generation (H2O2) and lipid peroxidation (MDA) compared to non-Pb stressed seedlings. However, increased antioxidants in the NPs treatments such as SOD, CAT, POD and proline content, scavenged these ROS. Considering all the parameters under study, priming alleviated Pb stress in the following order: FeNPs > ZnNPs > hydropriming > control. To summarise, seed priming with Zn- and Fe-NPs has the potential to alleviate Pb toxicity via reduced Pb uptake, ROS generation and lipid peroxidation as well as increased proline content and activation of antioxidant enzymatic system.
Integrated Analysis of Transcriptome and Metabolome Reveals New Insights into the Formation of Purple Leaf Veins and Leaf Edge Cracks in Brassica juncea
Authors: Zhang Kaijing , Yang Dekun , Hu Yuchao , Njogu Martin Kagiki , Qian Jingjing , Jia Li , Yan Congsheng , Li Ziang , Wang Xing , Wang Liping
Published: August 2022

Purple leaf veins and leaf edge cracks comprise the typical leaf phenotype of Brassica juncea; however, the molecular mechanisms and metabolic pathways of the formation of purple leaf veins and leaf edge cracks remain unclear. In this study, transcriptome and metabolome analyses were conducted to explore the regulation pathway of purple leaf vein and leaf edge crack formation based on four mustard samples that showed different leaf colors and degrees of cracking. The results showed genes with higher expression in purple leaf veins were mainly enriched in the flavonoid biosynthesis pathway. Integrating related genes and metabolites showed that the highly expressed genes of ANS (BjuA004031, BjuB014115, BjuB044852, and BjuO009605) and the excessive accumulation of dihydrokaempferol and dihydroquercetin contributed to the purple leaf veins by activating the synthetic pathways of pelargonidin-based anthocyanins and delphinidin-based anthocyanins. Meanwhile, “alpha-farnesene synthase activity” and “glucan endo-1, 3-beta-D-glucosidase activity” related to the adversity were mainly enriched in the serrated and lobed leaves, indicating that the environmental pressure was the dominant factor controlling the change in leaf shape. Overall, these results provided new insights into the regulation pathways for formation of purple leaf veins and leaf edge cracks, which could better accelerate the theoretical research on purple leaf vein color and leaf edge cracks in mustard.
Deep Learning Utilization in Agriculture: Detection of Rice Plant Diseases Using an Improved CNN Model
Authors: Latif Ghazanfar , Abdelhamid Sherif E. , Mallouhy Roxane Elias , Alghazo Jaafar , Kazimi Zafar Abbas
Published: August 2022

Rice is considered one the most important plants globally because it is a source of food for over half the world’s population. Like other plants, rice is susceptible to diseases that may affect the quantity and quality of produce. It sometimes results in anywhere between 20–40% crop loss production. Early detection of these diseases can positively affect the harvest, and thus farmers would have to be knowledgeable about the various disease and how to identify them visually. Even then, it is an impossible task for farmers to survey the vast farmlands on a daily basis. Even if this is possible, it becomes a costly task that will, in turn, increases the price of rice for consumers. Machine learning algorithms fitted to drone technology combined with the Internet of Things (IoT) can offer a solution to this problem. In this paper, we propose a Deep Convolutional Neural Network (DCNN) transfer learning-based approach for the accurate detection and classification of rice leaf disease. The modified proposed approach includes a modified VGG19-based transfer learning method. The proposed modified system can accurately detect and diagnose six distinct classes: healthy, narrow brown spot, leaf scald, leaf blast, brown spot, and bacterial leaf blight. The highest average accuracy is 96.08% using the non-normalized augmented dataset. The corresponding precision, recall, specificity, and F1-score were 0.9620, 0.9617, 0.9921, and 0.9616, respectively. The proposed modified approach achieved significantly better results compared with similar approaches using the same dataset or similar-size datasets reported in the extant literature.
Draft Genome Sequence of Priestia sp. Strain TSO9, a Plant Growth-Promoting Bacterium Associated with Wheat (Triticum turgidum subsp. durum) in the Yaqui Valley, Mexico
Authors: Ortega-Urquieta Maria , Valenzuela-Ruíz Valeria , Mitra Debasis , Hyder Sajjad , Elsheery Nabil , Kumar Das Mohapatra Pradeep , Parra-Cota Fannie , de los Santos-Villalobos Sergio
Published: August 2022

Strain TSO9 was isolated from a commercial field of wheat (Triticum turgidum L. subsp. durum) located in the Yaqui, Valley, Mexico. Here, the genome of this strain was sequenced, obtaining a total of 5,248,515 bp; 38.0% G + C content; 1,186,514 bp N50; and 2 L50. Based on the 16S rRNA gene sequencing, strain TSO9 was affiliated with the genus Priestia. The genome annotation of Priestia sp. TSO9 contains a total of 147 RNAs, 128 tRNAs, 1 tmRNA, and 5512 coding DNA sequences (CDS) distributed into 332 subsystems, where CDS associated with agricultural purposes were identified, such as (i) virulence, disease, and defense (57 CDS) (i.e., resistance to antibiotics and toxic compounds (34 CDS), invasion and intracellular resistance (12 CDS), and bacteriocins and ribosomally synthesized antibacterial peptides (10 CDS)), (ii) iron acquisition and metabolism (36 CDS), and (iii) secondary metabolism (4 CDS), i.e., auxin biosynthesis. In addition, subsystems related to the viability of an active ingredient for agricultural bioproducts were identified, such as (i) stress response (65 CDS). These genomic traits are correlated with the metabolic background of this strain, and its positive effects on wheat growth regulation reported in this work. Thus, further investigations of Priestia sp. TSO9 are necessary to complement findings regarding its application in agroecosystems to increase wheat yield sustainably.
High Dietary Intake of Rye Affects Porcine Gut Microbiota in a Salmonella Typhimurium Infection Study
Authors: Hankel Julia , Chuppava Bussarakam , Wilke Volker , Hartung Clara Berenike , Muthukumarasamy Uthayakumar , Strowig Till , Bach Knudsen Knud Erik , Kamphues Josef , Visscher Christian
Published: August 2022

Bacterial fermentation of undigested carbohydrates in the hindgut has considerable potential for the stimulation or inhibition of the growth of distinct bacteria within microbiota. The aim of the present study was to evaluate whether high levels of rye affect porcine gut microbiota composition with subsequent effects on the load of Salmonella Typhimurium, an intestinal pathogen with zoonotic relevance. Therefore, forty-two 25-day-old piglets were allocated to two groups and fed a diet containing either 69% wheat or 69% rye for 35 days. One week after introducing the two different diets, the piglets were experimentally infected with Salmonella Typhimurium. The microbiota composition of cecal and fecal samples of the piglets were evaluated 28 days after infection. In the cecum, promoted growth of Bifidobacterium, several lactic acid bacteria and Faecalibacterium prausnitzii were seen in pigs fed the diet containing 69% rye. Bacterial species belonging to the genera Bifidobacterium and Catenisphaera were associated with differing bacterial counts of Salmonella Typhimurium detected in the cecal contents of all piglets in both feeding groups via cultural cultivation. The high intake of rye instead of wheat seems to promote the growth of beneficial intestinal bacteria accompanied by impaired growth conditions for the foodborne pathogen Salmonella Typhimurium.
Accumulation of Wheat Phenolic Acids under Different Nitrogen Rates and Growing Environments
Authors: Tian Wenfei , Wang Fengju , Xu Kaijie , Zhang Zhaoxing , Yan Junliang , Yan Jun , Tian Yubing , Liu Jindong , Zhang Yan , Zhang Yong , He Zhonghu
Published: August 2022

The health benefits of whole wheat grains are partially attributed to their phenolic acid composition, especially that of trans-ferulic acid (TFA), which is a powerful natural antioxidant. Breeders and producers are becoming interested in wheat with enhanced health-promoting effects. This study investigated the effects of different nitrogen (N) application rates (0, 42, 84, 126, and 168 N kg ha−1) on the phenolic acid composition of three wheat varieties in four locations for two years. The results indicate that the different N rates did not affect the TFA concentration but that they significantly affected the concentrations of para-coumaric acid, sinapic acid, and cis-ferulic acid in the wheat grains. A statistical analysis suggested that the wheat phenolic acid composition was predominantly determined by wheat variety, though there existed some interaction effect between the wheat variety and environments. The TFA concentration of the variety Jimai 22 was generally higher (with a mean value of 726.04 µg/g) but was easily affected by the environment, while the TFA concentration of the variety Zhongmai 578 (with a mean value of 618.01 µg/g) was more stable across the different environments. The results also suggest that it is possible to develop new wheat varieties with high yield potential, good end-use properties, and enhanced nutraceutical values.
Genome-Wide Identification and Expression Analysis of Isopentenyl transferase Family Genes during Development and Resistance to Abiotic Stresses in Tea Plant (Camellia sinensis)
Authors: Zhang Liping , Li Min , Fu Jianyu , Huang Xiaoqin , Yan Peng , Ge Shibei , Li Zhengzhen , Bai Peixian , Zhang Lan , Han Wenyan , Li Xin
Published: August 2022

The tea plant is an important economic crop and is widely cultivated. Isopentenyl transferase (IPT) is the first and rate-limiting enzyme of cytokinin (CK) signaling, which plays key roles in plant development and abiotic stress. However, the IPT gene family in tea plants has not been systematically investigated until now. The phylogenetic analyses, gene structures, and conserved domains were predicted here. The results showed that a total of 13 CsIPT members were identified from a tea plant genome database and phylogenetically classified into four groups. Furthermore, 10 CsIPT members belonged to plant ADP/ATP-IPT genes, and 3 CsIPTs were tRNA-IPT genes. There is a conserved putative ATP/GTP-binding site (P-loop motif) in all the CsIPT sequences. Based on publicly available transcriptome data as well as through RNA-seq and qRT-PCR analysis, the CsIPT genes which play key roles in the development of different tissues were identified, respectively. Furthermore, CsIPT6.2 may be involved in the response to different light treatments. CsIPT6.4 may play a key role during the dormancy and flush of the lateral buds. CsIPT5.1 may play important regulatory roles during the development of the lateral bud, leaf, and flower. CsIPT5.2 and CsIPT6.2 may both play key roles for increased resistance to cold-stress, whereas CsIPT3.2 may play a key role in improving resistance to high-temperature stress as well as drought-stress and rewatering. This study could provide a reference for further studies of CsIPT family’s functions and could contribute to tea molecular breeding.
Effect of Coal Blending on Ash Fusibility and Slurryability of Xinjiang Low-Rank Coal
Authors: Li Hui , Song Xiaoling , Li Gang , Kong Lingxue , Li Huaizhu , Bai Jin , Li Wen
Published: August 2022

This work investigated the effect of coal blending on ash fusibility and slurryability of Xinjiang low-rank coal. The results showed that Xinjiang low-rank coals were characterized by high internal water content, high volatile content, high ash fusing point, and poor slurryability, which can not be directly used in coal water slurry gasification. The blending method not only reduced the ash fusibility but also improved the slurryability of these low-rank coals. When the coals with low calcium and high silicon contents (KG and YK) were blended with coal with high calcium content (SH), the ash fusion temperatures of the blended coal were significantly reduced. Moreover, the SH coal showed the worst slurryability performance with a concentration of 48.56%. The slurryability of HS coal can be dramatically improved by blending with KG. When the mass fraction of KG coal reached 70%, the concentration of coal water slurry increased by 11%. For the blended coal of KG and YK, the concentration and stability of coal water slurry gradually increase with the increasing mass ratio of KG. The coal blending method can effectively improve the concentration of coal water slurry for the low-rank coals, which were difficult-to-prepare slurry.
Online Pyrometry Calibration for Industrial Combustion Process Monitoring
Authors: Zhou Chenchen , Wang Shaoqi , Cao Yi , Yang Shuang-Hua , Bai Bin
Published: August 2022

Temperature and its distribution are crucial for combustion monitoring and control. For this application, digital camera-based pyrometers become increasingly popular, due to its relatively low cost. However, these pyrometers are not universally applicable due to the dependence of calibration. Compared with pyrometers, monitoring cameras exist in all most every combustion chamber. Although these cameras, theologically, have the ability to measure temperature, due to lack of calibration they are only used for visualization to support the decisions of operators. Almost all existing calibration methods are laboratory-based, and hence cannot calibrate a camera in operation. This paper proposes an online calibration method. It uses a pre-calibrated camera as a standard pyrometer to calibrate another camera in operation. The calibration is based on a photo taken by the pyrometry-camera at a position close to the camera in operation. Since the calibration does not affect the use of the camera in operation, it sharply reduces the cost and difficulty of pyrometer calibration. In this paper, a procedure of online calibration is proposed, and the advice about how to set camera parameters is given. Besides, the radio pyrometry is revised for a wider temperature range. The online calibration algorithm is developed based on two assumptions for images of the same flame taken in proximity: (1) there are common regions between the two images taken at close position; (2) there are some constant characteristic temperatures between the two-dimensional temperature distributions of the same flame taken from different angles. And those two assumptions are verified in a real industrial plants. Based on these two verified features, a temperature distribution matching algorithm is developed to calibrate pyrometers online. This method was tested and validated in an industrial-scale municipal solid waste incinerator. The accuracy of the calibrated pyrometer is sufficient for flame monitoring and control.
Synthetic-Gas Production through Chemical Looping Process with Concentrating Solar Dish: Temperature-Distribution Evaluation
Authors: Montà Edoardo , Santarelli Massimo , Papurello Davide
Published: August 2022

The energy crisis and the adaptation of the global energy structure promote the development of renewable energies, in particular solar energy, also for syngas production. In this work, attention was focused on solar devices, necessary to provide high-temperature heat for the reduction reaction of metal oxides involved in the chemical looping driven by solar energy. Thermochemical processes for synthetic-gas production and CO2 sequestration were investigated using a concentrating solar thermal system. This paper proposes a useful forecasting model of the receiver temperature to make a realistic estimate of the system’s producibility for the different periods of the year. The model proposed was validated in the winter season, and the predicted temperature varied below 5% considering the real experimental data (442–472 °C). The validated model was used to evaluate the temperature receiver in spring and in summer, when the thermal level is reliable for thermochemical processes. From the spring season until the completion of the summer season, optimum conditions inside the receiver were reached (above 1000 °C). These preliminary findings could be used for the development of large-scale production systems.
Study of Torsional Vibration Bifurcation Characteristics of Direct-Drive Wind Turbine Shaft System
Authors: Huang Zhonghua , Wu Rongjie , Chen Jinhao , Xu Xin , Xie Ya
Published: August 2022

This paper set out to establish the dynamics model of shaft torsional vibration for direct-drive wind turbine with the phenomenon of unstable shaft system torsional vibration. The stability of the equilibrium point of the dynamical model is investigated, and the Routh–Hurwitz stability criterion is used to obtain a range of values for the bifurcation control parameters. For the stable equilibrium point, the stability domain of the system is calculated by constructing the Lyapunov function. The sensitivity analysis of system parameters is carried out to obtain the law of the effect of system parameters on system stability of the torsional vibration system. The results are substituted for example calculations, and the results verify the correctness of the theoretical analysis conclusions. It is proved that it is feasible to analyze the torsional vibration characteristics of the direct-drive wind turbine shaft system by using the principle of Routh–Hurwitz stability, etc., which provides a reference for the structural design of direct-drive wind turbine.
Morula Tree: From Fruit to Wine through Spontaneous Fermentation and the Potential of Deriving Other Value-Added Products
Authors: Legodi Lesetja Moraba , Lekganyane Maleho Annastasia , Moganedi Kgabo L. Maureen
Published: August 2022

Sclerocarya birrea (Morula tree) is one of the indigenous trees bearing wild fruits with various applications in the African communities. Wine is a globally known beverage usually made from grapes; however, recently, other fruits, including wild fruits with a considerable amount of sugars, can be used for making wines. The marula fruit wine is also important in many communities for cultural activities and can be enjoyed by people of varying age groups depending on the age of the product. In recent years, there has been growing interest in shifting from traditional marula winemaking to developing technologies for the marula winemaking process and commercialisation. The process of marula winemaking is similar to the production of grape wines, which entails collection, selection and washing of the fruits; extraction of the juice and mashing; formation and removal of the scum; and ultimately spontaneous fermentation of the resulting juice. The new process in marula winemaking would take into consideration the use of starter cultures as either monoculture or mixed cultures developed from the native marula fruit microbiota and the pasteurisation of the juice. The main challenge or difficulty with marula is the extraction of sugar and other soluble solids from the pulp more than it is for the grapes. The other challenge confronting the sustainability of marula wine is the seasonality of the fruit and poor juice yield. It is therefore imperative to develop strategies to increase the juice yield without affecting the quality, to preserve the marula fruits to ensure the year-round presence of marula fruit wine in the markets and, consequently, to improve the income generation capacity of the households dependent on the product. In addition to achieving a high juice yield, it is imperative to ensure consistent quality wine products. This review gives an overview of the S. birrea subsp. caffra and the biochemical components of the fruits or juice. It also highlights the use of marula fruits for wine production in African communities. The potential economic sustainability of the marula fruit wine is explored, particularly in southern Africa, where the marula tree (Morula) is abundant and the marula fruit wine is popularly produced. The review also examines the opportunities, challenges and future prospects of the marula fruit wine.
Intelligent Facemask Coverage Detector in a World of Chaos
Authors: Waziry Sadaf , Wardak Ahmad Bilal , Rasheed Jawad , Shubair Raed M. , Yahyaoui Amani
Published: August 2022

The recent outbreak of COVID-19 around the world has caused a global health catastrophe along with economic consequences. As per the World Health Organization (WHO), this devastating crisis can be minimized and controlled if humans wear facemasks in public; however, the prevention of spreading COVID-19 can only be possible only if they are worn properly, covering both the nose and mouth. Nonetheless, in public places or in chaos, a manual check of persons wearing the masks properly or not is a hectic job and can cause panic. For such conditions, an automatic mask-wearing system is desired. Therefore, this study analyzed several deep learning pre-trained networks and classical machine learning algorithms that can automatically detect whether the person wears the facemask or not. For this, 40,000 images are utilized to train and test 9 different models, namely, InceptionV3, EfficientNetB0, EfficientNetB2, DenseNet201, ResNet152, VGG19, convolutional neural network (CNN), support vector machine (SVM), and random forest (RF), to recognize facemasks in images. Besides just detecting the mask, the trained models also detect whether the person is wearing the mask properly (covering nose and mouth), partially (mouth only), or wearing it inappropriately (not covering nose and mouth). Experimental work reveals that InceptionV3 and EfficientNetB2 outperformed all other methods by attaining an overall accuracy of around 98.40% and a precision, recall, and F1-score of 98.30%.
Mechanism Analysis and Potential Solutions for Casing Deformation of Shale GAS Fracturing Wells in Sichuan Basin
Authors: Xu Bihua , Yang Shuo , Yuan Bin , Ma Lu , Wang Leding
Published: August 2022

Casing deformation caused by fault and fracture sliding derived from fracturing has attracted growing attention. Casing deformation frequently occurs during the hydraulic fracturing process in the Sichuan Basin. Although its mechanism has been intensively studied, this issue is becoming increasingly severe and demands immediate solutions, especially in the shale gas blocks of Changning-Weiyuan-Zhaotong. The present study summarizes and analyzes the research progress relevant to casing deformation based on the existing literature. It is shown that the casing deformation rate of the deflection point on the shale gas horizontal well is much higher than that of other places and that shear deformation is the dominant form. The main factors influencing the casing deformation of shale gas horizontal wells include weakened strength of the collapsing casing, geological factors, cement, cement quality sheath, fracturing engineering factor, etc. We propose to reduce casing deformation by optimizing well trajectory, improving casing strength and cementing quality or optimizing fracturing operation. In addition, a hierarchical relationship between the influencing factors is also provided. However, the mechanisms of some forms of casing deformation need to be further studied, and the casing deformation in shale gas exploitation must be solved urgently.
Extraction, Chemical Compositions and Biological Activities of Essential Oils of Cinnamomum verum Cultivated in Vietnam
Authors: Phu Hiep Hoang , Pham Van Khang , Tran Thien Hien , Pham Dung Thuy Nguyen
Published: August 2022

Cinnamomum verum (Cinnamomum genus) essential oil is commonly used in food preparation and traditional medicines, with a broad spectrum of biological activities. However, research on the extraction of essential oils (EOs) from C. verum cultivated locally in Vietnam is currently limited. Therefore, in this study, the chemical compositions and bioactivities of EOs from the bark and leaves of C. verum collected from the Thai Nguyen and Yen Bai provinces of Vietnam were investigated. The EOs samples were extracted by using water distillation, organic solvent (n-hexane) and ultrasound-assisted (in n-hexane solvent) extraction methods. The chemical composition of the obtained EOs were analyzed by GC-FID and GC/MS analyses. Results showed that the major chemical compositions of C. verum EOs were: (E)-cinnamaldehyde, trans-cinnamic acid, cinnamyl acetate, and benzaldehyde. Furthermore, C. verum EOs exhibited inhibitory activities against two tested cancer cell lines and four bacterial strains. These findings provide essential knowledge about the potential application of C. verum EOs cultivated in Vietnam for the pharmaceutical industry.
Adsorption and Self-Diffusion of R32/R1234yf in MOF-200 Nanoparticles by Molecular Dynamics Simulation
Authors: Jing Biyu , Xia Di , Wang Guoqiang
Published: August 2022

The thermophysical properties of a refrigerant can be modified via adding metal organic frameworks (MOF) to it. Understanding the adsorption–diffusion process of the mixture in MOFs at the molecular level is important to further improve the efficiency of the organic Rankine cycle. The adsorption and diffusion of R32/R1234yf in MOF-200 was investigated by molecular dynamics simulation in the present work. The results show that the number of adsorbed molecules of R32 in MOF-200 per unit mass is higher than that of R1234yf in the pure fluid adsorption system. The adsorption capacity of the mixture is lower than that of a pure working medium due to competitive adsorption. For both pure and mixed refrigerants, the adsorption heat of R32 in MOF-200 is smaller than that of R1234yf. Compared with R1234yf, the self-diffusion coefficient of R32 in MOF-200 is larger because of the lower diffusion activation energy.
Uncertainty Propagation Based MINLP Approach for Artificial Neural Network Structure Reduction
Authors: Sildir Hasan , Sarrafi Sahin , Aydin Erdal
Published: August 2022

The performance of artificial neural networks (ANNs) is highly influenced by the selection of input variables and the architecture defined by hyper parameters such as the number of neurons in the hidden layer and connections between network variables. Although there are some black-box and trial and error based studies in the literature to deal with these issues, it is fair to state that a rigorous and systematic method providing global and unique solution is still missing. Accordingly, in this study, a mixed integer nonlinear programming (MINLP) formulation is proposed to detect the best features and connections among the neural network elements while propagating parameter and output uncertainties for regression problems. The objective of the formulation is to minimize the covariance of the estimated parameters while by (i) detecting the ideal number of neurons, (ii) synthesizing the connection configuration between those neurons, inputs and outputs, and (iii) selecting optimum input variables in a multi variable data set to design and ensure identifiable ANN architectures. As a result, suggested approach provides a robust and optimal ANN architecture with tighter prediction bounds obtained from propagation of parameter uncertainty, and higher prediction accuracy compared to the traditional fully connected approach and other benchmarks. Furthermore, such a performance is obtained after elimination of approximately 85% and 90% of the connections, for two case studies respectively, compared to traditional ANN in addition to significant reduction in the input subset.
Entropy Flow Analysis of Thermal Transmission Process in Integrated Energy System Part I: Theoretical Approach Study
Authors: Chen Changnian , Wang Junjie , Zhao Haoran , Yu Zeting , Han Jitian , Chen Jian , Liu Chunyang
Published: August 2022

It is very important to accurately describe the dynamic processes of thermal energy transmission for coupling with Integrated Energy System (IES). In order to study the thermodynamic characteristics of heat supply, this paper theoretically suggested a generalized model of entropy flow by deducing the expression of entropy conduction and convection based on thermodynamic law and heat transfer analysis. Taking temperature and entropy as the intensity and extension properties, the equivalent distributed and lumped parameter models are established to describe the features of heat loss and transmission delay. The effectiveness of current models is verified by comparing with solutions of conventional Partial Differential Equations (PDE) of heat transfer. The numerical simulation and verification procedure were conducted by Matlab/simulink. The proposed models were applied to simulate the response of temperature and entropy flow of a pipe with length of 100 m under different discrete conditions. The results show that for a distributed parameter model the maximum relative error is 1.275% when the pipe is divided into 100 sections, and for a lumped parameter model, the overall relative error is in the order of 10−3, which can be ignored in practical applications. All these prove the correctness of proposed models in this paper.
KPLS-Based Mach Number Prediction for Multi-Mode Wind Tunnel Flow System
Authors: Yuan Ping , Zhao Luping
Published: August 2022

In wind tunnels, the Mach number needs to be precisely monitored and controlled. It is difficult to obtain the Mach number directly online, especially when the wind tunnel system is operating in multiple modes. To deal with this problem, a Mach number prediction algorithm based on the kernel partial least squares method is proposed for multi-mode wind tunnel systems. First, in order to reflect real-time changes, the time-slice partial least squares regression method is adopted. Then, in order to enable the model to represent information about the whole working mode divided by key process variables, the mean-value partial least squares model is established and is compared with the time-slice model. Then, considering that wind tunnel systems exhibit strong nonlinear characteristics, the kernel partial least squares method, which is suitable for nonlinear systems, is used to predict the Mach number. The results show that the mean-value model is better than the time-slice model, the models for single modes show better prediction abilities than those for multiple modes, and the kernel partial least square method is more suitable for wind tunnel systems than the partial least square method.
Missed Opportunities for Growth in the Posttraumatic Helping Environment: The Role of Spirituality
Authors: Wilmshurst Kaitlin , Hovey Angela , Brownlee Keith
Published: August 2022

This paper focuses on social work’s understanding of how posttraumatic counselling may help or hinder recovery from trauma. A qualitative case study was conducted using an autobiographic memoir that provides an in-depth personal narrative of one woman’s experience of trauma, posttraumatic stress disorder, the posttraumatic helping environment, and healing journey. Inductive thematic analysis uncovered themes that align with the existing literature. Novel or understudied aspects for consideration also emerged, including the importance of psychoeducation, behavioural activation, and secondary factors related to the posttraumatic environment that impede healing. The analysis highlighted missed opportunities to clinically address issues of identity and meaning in a spiritually sensitive manner. Although the narrator made it clear to helping professionals that she was struggling with religious beliefs and was in spiritual crisis, helping professionals seemed to eschew exploration of these concerns. Implications for clinical social work practice and future research are discussed.
Apocryphal Gospel Titles in Coptic
Authors: Falkenberg René
Published: August 2022

During the 2nd–5th centuries, the usual format of the canonical gospel title is “The Gospel According to [person]”. While becoming well-established in this period, the title is reused and transformed when naming the apocryphal gospels. In order to study the meaning of the emerging canonical and apocryphal gospel titles, the claims of these titles will be analysed to determine who each title presents as the gospel’s source (often a divine figure) and who is implied to be that gospel’s author (often a human person). By revisiting well-known apocryphal gospels, and expanding on their number, new insights are achieved regarding the role of titles, authors, and apocryphal gospels. Results concern, for instance, the long recension of the Apocryphon of John, whose title comes to display a prominent gospel title; the Gospel of Judas, of which the author may be the infamous Judas himself; and the Gospel of Truth, which may not be an apocryphal gospel at all.
The Self as Source and Destination for Intuitive Interpretations of Religious or Spiritual Experiences
Authors: Oberg Andrew
Published: August 2022

Religious or spiritual experiences (RSE) are often difficult to fully express even if one might be able to describe particular aspects of them. Yet the influences that such carry in a person’s mode of being can be vast, and they are clearly a fundamental part of the human condition (whether accepted, denied, or dismissed, their occurrence appears universal). How then might these RSE—and the corresponding grounding implications—be better explained? This paper seeks to elucidate the problematic via an applied investigation of a self-theoretical framework which is composed of three interlaced “sets”: (1) Self-defining traits, (2) Self-directing traits, and (3) Self-evaluating traits. We will suggest that these elements (with consciousness and bodily presence) form a core self that is a separable facet from those of personal identity and whole person; and this finding will in turn require a brief look at consciousness and a two-tiered mental model. Taking the self-view into a phenomenological hermeneutical examination will illuminate the position at which RSE might reside within an individual’s cognition, and thence to exploring the pre-thought (the functionally pre-aware) foundations involved. Finally, some considerations will be given for how an understanding of the foregoing structure (if it be found valid) might contribute towards the purposive shifting of that self-basis from out of and towards which RSE are situated in a lifeworld.
Exploring the Influence of Government Data Performance on Knowledge Capabilities: Towards a Data-Oriented Political Economy
Authors: Mukhametov Daniyar
Published: August 2022

This article is devoted to the study of the influence of government data performance on knowledge capabilities. Knowledge capabilities play a key role in open innovation and creation of citizen-oriented products and services. However, it is necessary to assess the role of the information environment in the development of knowledge capabilities, including government data as a product and a component of the information environment. Government data performance is expressed through the statistical capacity score and its three dimensions: periodicity assessment of statistical capacity, methodology assessment of statistical capacity, and source data assessment of statistical capacity. Knowledge capabilities are expressed through economic complexity, which reflects the diversity and uniqueness of the production capabilities inherent in each country’s exports. Econometric analysis is based on dynamic panel data models that quantify the effect of government data performance on economic complexity. The final dataset includes 94 countries and their indicators for the selected variables for 2004–2019. The models show that government data performance and its various dimensions influence economic complexity because government data provide a detailed and publicly available description of the economic space, including available resources and potential tasks. Based on these data, agents can produce dissimilar and unique products. This logic may be true in general for the influence of government data performance on knowledge capabilities: structured and complete government data reduces the cost of information analysis and provides information support for decisions. The results of the study contribute to the ideas of a data-oriented political economy. Government participation in value creation includes various forms of indirect influence. The provision of government data is one of these forms. The development of collective data governance and collaborative data projects makes it possible to create more complete datasets and stimulates citizen involvement and deliberation.
Human-Centred Design in UK Asylum Social Protection
Authors: James Michelle L. , Forrester-Jones Rachel
Published: August 2022

This paper considers United Kingdom welfare provision for asylum seekers in the context of social protection scholarship, policy discourse more commonly associated with international development. Social protection definitions are contested, ranging from those focused on state provision to wider interpretations reflecting debates on holistic wellbeing, human rights and self-actualisation. Most recently, the 2030 Agenda for Sustainable Development has called for social protection policies for all citizens to reduce inequality among and within countries. Though there is exigency to reduce the extreme inequality existing between countries, literature is lacking on how social protection can be used to critique inequality within more economically affluent nations. Commentaries on social protection also tend to focus on economic poverty, with less attention given to vulnerabilities such as marginalisation. Literature suggests that UK asylum welfare provision is based on deterrence, control and marginalisation. In response, and to encourage equity in how all countries’ public policy is assessed, this paper utilises an international social protection framework to critique UK asylum welfare provision. It concludes by advocating for transdisciplinary, human-centred and comprehensive social protection policy design, encouraging participation by a wider range of stakeholders and a holistic understanding of wellbeing to meet asylum seekers’ needs effectively and efficiently.
The Influence of Governmental Agricultural R&D Expenditure on Farmers’ Income—Disparities between EU Member States
Authors: Stoian Mirela , Ion Raluca Andreea , Turcea Vlad Constantin , Nica Ionut Catalin , Zemeleaga Catalin Gheorghe
Published: August 2022

This article investigates how governmental agricultural R&D expenditure affect economic prosperity and sustainable development, attempting to verify the hypothesis that agricultural research and development expenditures are among the key factors influencing the farmers’ income, as one of the sustainable development indicators. Statistical data were retrieved from European international databases for the period of 2004–2020 and were analyzed using the regression model. The results of the study indicate positive effects for most of the EU member states. The countries where the results validate the hypothesis are Austria, Belgium, Bulgaria, the Czech Republic, Germany, Estonia, Finland, France, Greece, Croatia, Ireland, Latvia, Poland, Slovakia, Slovenia, and the United Kingdom, as a former member state of the EU. Further, the model confirms that a significant portion of farmers’ income growth is explained by the governmental R&D expenditure. These findings may change the methods and directions regarding the agricultural R&D expenditure, underpinning the macroeconomic policy and agriculture in rural areas along the pathway to achieving the sustainable development goals.
Expenditure Responsibility Assignment and High-Quality Equity of Compulsory Education—Empirical Analysis Based on OECD Countries
Authors: Yu Wenjie , Ma Hongfan
Published: August 2022

Education for sustainable development poses high challenges to governments and public finance. Compared with OECD countries, China’s local governments bear too much expenditure responsibilities with respect to compulsory education, which theoretically affects the high-quality equity of compulsory education. Through empirical analysis using cross-country data with the panel spatial model, it is found that the proportion of central government expenditure and the government’s educational effort both have a steady and negative impact on the regional variable coefficient of compulsory education completion rate. Unitary or federal regime does not have a significant impact on the result. This paper suggests establishing a sharing financing system among all levels of government. According to the minimum standard guarantee principle of basic public services, the central government, which has the strongest fiscal capacity, should establish the national standard and take the responsibility on coordinating and balancing education service among regions and promoting the inter-regional equity. Local governments are encouraged to provide education services above national standard in accordance with their fiscal capacities.
SPDIAM: Methodology for Describing and Solving Spatial Problems in Territorial Planning
Authors: Germanaite Indraja , Zaleckis Kestutis , Butleris Rimantas
Published: August 2022

Spatial pattern (SP) helps to analyze the tasks and provisions that arise in the spatial planning and design disciplines examining a complex spatial system (CSS). The aim of this article is to present a territorial planning process and how SP description, identification, and application methodology (SPDIAM) can help to work with it using a CSS model. First, the quantitative spatial analysis methods and spatial network analysis tools that can be used to identify SP are compared with SPDIAM. Then, the main concepts of SPDIAM and created IT artefacts are explained. In the experiment section, the SP is identified using spatial metapatterns in different North American, European, and African cities and the correlation results of SP and statistics are calculated to show a medium to close relationship. Then, the territorial planning cycle and SPDIAM application use case using the data of Kaunas city (Lithuania) are presented. The results of SPDIAM can be used to associate the shape of the territory with the geographer models and Alexander patterns using the bottom-up modelling principle and allows us to standardize urban planning solutions.