bluuebunny/crossref_metadata_2025 huggingface dataset:
The Colonization and Effect of Isaria cateinannulata on Buckwheat Sprouts
Authors: Zhang Xiaona , Peng Xue , Yang Guimin , Chen Qingfu , Jin Daochao
Published: December 2022

The use of entomogenous fungi as endophytes is currently an area of active research. Isaria cateniannulata is an important entomogenous fungus that has been employed for the active control of a range of pests in agricultural and forestry settings, but its direct impact on plants remains to be evaluated. Herein, we assessed the ability of I. cateniannulata to colonize buckwheat, Fagopyrum esculentum and F. tataricum, and its impact on buckwheat defense enzyme activity and physiological indexes. The majority of fungal submerge condia was able to enter into leaves through stomata and veins, and this was followed by conidial attachment, lytic enzyme secretion, conidial deformation, and enhanced defensive enzyme activity within buckwheat, followed by the repair of damaged tissue structures. I. cateniannulata populations on buckwheat leaf surfaces (in CFU/g) reached the minimum values at 24 h after inoculation. At this time, the blast analysis revealed that the sequence identity values were 100%, which was consistent with the sequence of I. cateniannula. The number of I. cateniannulata submerge conidia colonized in the buckwheat leaves gradually rose to peak levels on 7 d post-inoculation, and then gradually declined until 10 d, at which time the buckwheat plant growth index values increased. This study provided novel evidence that I. cateniannulata could be leveraged as an endophytic fungus capable of colonizing buckwheat plants and promoting their growth.
Tissue-Specific Profiling of Biflavonoids in Ginkgo (Ginkgo biloba L.)
Authors: Kovač Tomas Marija , Jurčević Iva , Šamec Dunja
Published: December 2022

Biflavonoids are flavonoid dimers that are much less studied than monomeric flavonoids. Their precise distribution among plants and their role in plants is still unknown. Here, we have developed a HPLC-DAD method that allows us to separate and simultaneously determine the five major biflavonoids (amentoflavone, bilobetin, ginkgetin, isoginkgetin, and sciadopitysin) in ginkgo (Ginkgo biloba L.). We performed tissue-specific profiling of biflavonoids in ten different plant parts: tree bark, twigs bark, twigs without bark, buds, leaf petioles, leaf blades, seed stalks, sarcotesta, nutshells, and kernels. We did not detect biflavonoids in plant parts not in direct contact with the environment (twigs without bark, nutshells, and kernels). We found the highest total biflavonoids content in leaves, where sciadopitysin was predominant. In contrast, in the bark, amentoflavone was the predominant biflavonoid, suggesting that more methylated biflavonoids accumulate in leaves and seeds. This is probably related to their biological function, which remains to be determined.
CD34 Antibody-Coated Biodegradable Fiber Membrane Effectively Corrects Atrial Septal Defect (ASD) by Promoting Endothelialization
Authors: Chu Bin , Li Xiaoli , Fan Shiqiang , He Jinmei , Ge Xiaohong , Li Hui , Chen Changsheng , Wang Zhen , Wang Song , Li Boning
Published: December 2022

Biodegradable materials are a next-generation invention for the treatment of congenital heart diseases. However, the corresponding technology used to develop ideal biomaterials still presents challenges. We previously reported the first biodegradable atrial septal defect (ASD) occluder made of poly-lactic acid (PLLA). Unfortunately, the PLLA occluder had a limited endothelialization effect. In this study, the surface of the occluder membrane was coated with sericin/CD34 antibodies to promote the growth of endothelial cells and the regeneration of defective tissue and enhance the repair of the atrial septal defect. The physicochemical properties of the coat on the surface of the fiber membrane were characterized. The sericin coat successfully covered the fiber surface of the membrane, and the thickness of the membrane increased with the sericin concentration. The swelling rate reached 230%. The microscopic observation of fluorescently labeled CD34 antibodies showed that the antibodies successfully attached to the fiber membrane; the fluorescence intensity of PLLA-SH5 was particularly high. The in vitro experiment showed that the PLLA-SH-CD34 fiber membrane was biocompatible and promoted the adhesion and proliferation of endothelial cells. According to our findings, the PLLA-SH-CD34 membrane provides a theoretical and technical basis for the research and development of novel biodegradable occluders.
Open-Celled Foams from Polyethersulfone/Poly(Ethylene Glycol) Blends Using Foam Extrusion
Authors: Raje Aniket , Georgopanos Prokopios , Koll Joachim , Lillepärg Jelena , Handge Ulrich A. , Abetz Volker
Published: December 2022

Polyethersulfone (PESU), as both a pristine polymer and a component of a blend, can be used to obtain highly porous foams through batch foaming. However, batch foaming is limited to a small scale and is a slow process. In our study, we used foam extrusion due to its capacity for large-scale continuous production and deployed carbon dioxide (CO2) and water as physical foaming agents. PESU is a high-temperature thermoplastic polymer that requires processing temperatures of at least 320 °C. To lower the processing temperature and obtain foams with higher porosity, we produced PESU/poly(ethylene glycol) (PEG) blends using material penetration. In this way, without the use of organic solvents or a compounding extruder, a partially miscible PESU/PEG blend was prepared. The thermal and rheological properties of homopolymers and blends were characterized and the CO2 sorption performance of selected blends was evaluated. By using these blends, we were able to significantly reduce the processing temperature required for the extrusion foaming process by approximately 100 °C without changing the duration of processing. This is a significant advancement that makes this process more energy-efficient and sustainable. Additionally, the effects of blend composition, nozzle temperature and foaming agent type were investigated, and we found that higher concentrations of PEG, lower nozzle temperatures, and a combination of CO2 and water as the foaming agent delivered high porosity. The optimum blend process settings provided foams with a porosity of approximately 51% and an average foam cell diameter of 5 µm, which is the lowest yet reported for extruded polymer foams according to the literature.
Multifunctional Oxidized Succinoglycan/Poly(N-isopropylacrylamide-co-acrylamide) Hydrogels for Drug Delivery
Authors: Hu Yiluo , Shin Younghyun , Park Sohyun , Jeong Jae-pil , Kim Yohan , Jung Seunho
Published: December 2022

We prepared the self-healing and temperature/pH-responsive hydrogels using oxidized succinoglycan (OSG) and a poly (N-isopropyl acrylamide-co-acrylamide) [P(NIPAM-AM)] copolymer. OSG was synthesized by periodate oxidation of succinoglycan (SG) isolated directly from soil microorganisms, Sinorhizobium meliloti Rm1021. The OSG/P(NIPAM-AM) hydrogels were obtained by introducing OSG into P(NIPAM-AM) networks. The chemical structure and physical properties of these hydrogels were characterized by ATR-FTIR, XRD, TGA, and FE-SEM. The OSG/P(NIPAM-AM) hydrogels showed improved elasticity, increased thermal stability, new self-healing ability, and 4-fold enhanced tensile strength compared with the P(NIPAM-AM) hydrogels. Furthermore, the 5-FU-loaded OSG/P(NIPAM-AM) hydrogels exhibited effective temperature/pH-responsive drug release. Cytotoxicity experiments showed that the OSG/P(NIPAM-AM) hydrogels were non-toxic, suggesting that OSG/P(NIPAM-AM) hydrogels could have the potential for biomedical applications, such as stimuli-responsive drug delivery systems, wound healing, smart scaffolds, and tissue engineering.
Reinforcing a Thermoplastic Starch/Poly(butylene adipate-co-terephthalate) Composite Foam with Polyethylene Glycol under Supercritical Carbon Dioxide
Authors: Chang Chih-Jen , Chandrasekar Jayashree , Cho Chia-Jung , Venkatesan Manikandan , Huang Pin-Shu , Yang Ching-Wei , Wang Hsin-Ta , Wong Chang-Ming , Kuo Chi-Ching
Published: December 2022

Biodegradable foams are a potential substitute for most fossil-fuel-derived polymer foams currently used in the cushion furniture-making industry. Thermoplastic starch (TPS) and poly(butylene adipate-co-terephthalate) (PBAT) are biodegradable polymers, although their poor compatibility does not support the foam-forming process. In this study, we investigated the effect of polyethylene glycol (PEG) with or without silane A (SA) on the foam density, cell structure and tensile properties of TPS/PBAT blends. The challenges in foam forming were explored through various temperature and pressure values under supercritical carbon dioxide (CO2) conditions. The obtained experimental results indicate that PEG and SA act as a plasticizer and compatibilizer, respectively. The 50% (TPS with SA + PEG)/50% PBAT blends generally produce foams that have a lower foam density and better cell structure than those of 50% (TPS with PEG)/50% PBAT blends. The tensile property of each 50% (TPS with SA + PEG)/50% PBAT foam is generally better than that of each 50% (TPS with PEG)/50% PBAT foam.
Fabrications of Electrospun Mesoporous TiO2 Nanofibers with Various Amounts of PVP and Photocatalytic Properties on Methylene Blue (MB) Photodegradation
Authors: Yoo Sun-Ho , Yoon Han-Sol , Han HyukSu , Na Kyeong-Han , Choi Won-Youl
Published: December 2022

The superior chemical and electrical properties of TiO2 are considered to be suitable material for various applications, such as photoelectrodes, photocatalysts, and semiconductor gas sensors; however, it is difficult to commercialize the applications due to their low photoelectric conversion efficiency. Various solutions have been suggested and among them, the increase of active sites through surface modification is one of the most studied methods. A porous nanostructure with a large specific surface area is an attractive solution to increasing active sites, and in the electrospinning process, mesoporous nanofibers can be obtained by controlling the composition of the precursor solution. This study successfully carried out surface modification of TiO2 nanofibers by mixing polyvinylpyrrolidone with different molecular weights and using diisopropyl azodicarboxylate (DIPA). The morphology and crystallographic properties of the TiO2 samples were analyzed using a field emission electron microscope and X-ray diffraction method. The specific surface area and pore properties of the nanofiber samples were compared using the Brunauer-Emmett-Teller method. The TiO2 nanofibers fabricated by the precursor with K-30 polyvinyl pyrrolidone and diisopropyl azodicarboxylate were more porous than the TiO2 nanofibers without them. The modified nanofibers with K-30 and DIPA had a photocatalytic efficiency of 150% compared to TiO2 nanofibers. Their X-ray diffraction patterns revealed anatase peaks. The average crystallite size of the modified nanofibers was calculated to be 6.27–9.27 nm, and the specific surface area was 23.5–27.4 m2/g, which was more than 150% larger than the 17.2 m2/g of ordinary TiO2 nanofibers.
Copper-Doped Carbon Nanodots with Superior Photocatalysis, Directly Obtained from Chromium-Copper-Arsenic-Treated Wood Waste
Authors: Xing Dan , Koubaa Ahmed , Tao Yubo , Magdouli Sara , Li Peng , Bouafif Hassine , Zhang Jingfa
Published: December 2022

An ecofriendly approach was developed for preparing copper-doped carbon dots (CDs) with superior photocatalysis using chromium-copper-arsenic (CCA)-treated wood waste as a precursor. Original wood (W-CDs), CCA-treated wood (C-CDs), and bioremediation CCA wood (Y-CDs) were used as the precursors. The chemical composition and structural, morphological, and optical properties, as well as the photocatalytic ability of the synthesized CDs varied with wood type. The C-CDs and W-CDs had similar characteristics: quasispherical in shape and with a diameter of 2 to 4.5 nm. However, the Y-CDs particles were irregular and stacked together, with a size of 1.5–3 nm. The presence of nitrogen prevented the formation of an aromatic structure for those CDs fabricated from bioremediation CCA wood. The three synthesized CDs showed a broad absorption peak at 260 nm and a weak absorption peak at 320 nm. Proof of the model study for the fabrication of luminescent CDs from CCA wood waste for bioimaging was provided. The degradation rate of CD photocatalytic MB was 97.8% for 30 min. Copper doping gives the CDs electron acceptor properties, improving their photocatalytic efficiency. This study provides novel ways to prepare nanomaterials from decommissioned wood as a nontoxic and low-cost alternative to fluorescent dots.
High-Temperature Response Polylactic Acid Composites by Tuning Double-Percolated Structures
Authors: Yao Haiwei , Xue Rong , Wang Chouxuan , Chen Chengzhi , Xie Xin , Zhang Pengfei , Zhao Zhongguo , Li Yapeng
Published: December 2022

Due to the properties of a positive temperature coefficient (PTC) effect and a negative temperature coefficient (NTC) effect, electrically conductive polymer composites (CPCs) have been widely used in polymer thermistors. A dual percolated conductive microstructure was prepared by introducing the polybutylene adipate terephthalate phase (PBAT) into graphene nanoplatelets (GNPs)-filled polylactic acid (PLA) composites, intending to develop a favorable and stable PTC material. To achieve this strategy, GNPs were selectively distributed in the PBAT phase by injection molding. In this study, we investigated the crystallization behavior, electrical conductivity, and temperature response of GNP-filled PLA/PBAT composites. The introduction of GNPs into PLA significantly increased PLA crystallization capacity, where the crystallization onset temperature (To) is raised from 116.7 °C to 134.7 °C, and the crystallization half-time (t1/2) decreases from 35.8 min to 27.3 min. The addition of 5 wt% PBAT increases the electrical conductivity of PLA/PBAT/GNPs composites by almost two orders of magnitude when compared to PLA/GNPs counterparts. The temperature of the heat treatment is also found to play a role in affecting the electrical conductivity of PLA-based composites. Increasing crystallinity is favorable for increasing electrical conductivity. PLA/PBAT/GNPs composites also show a significant positive temperature coefficient, which is reflected in the temperature–electrical resistance cycling tests.
Gas Pipeline Flow Prediction Model Based on LSTM with Grid Search Parameter Optimization
Authors: Liu Lu , Liang Jing , Ma Li , Zhang Hailin , Li Zheng , Liang Shan
Published: December 2022

Due to the abundant operation data (e.g., pressure, flow rate, and temperature) for natural gas (NG) gathering pipelines provided by the supervisory control and data acquisition (SCADA) system, the machine-learning-based real-time flow prediction has become a critical solution to enable the identification of the abnormality of pipelines, further to guarantee the safe operation of the pipelines. However, traditional machine-learning-based methods cannot always function well due to the temporal characteristics of the SCADA data often being ignored, resulting from a lack of time memory capability. Therefore, this paper proposes a method to automatically perform the feature mining of flow time series by considering the correlation of flow data at both ends of the pipeline, combined with the long short-term memory (LSTM) network. The current and historical data at both pipeline ends are used as input vectors of the LSTM network to predict the terminal output flow at the next moment. Furthermore, to solve the problem that the parameters of the LSTM model are configured with manual experience, a grid search algorithm (GSA) is introduced to optimize the parameters of the LSTM. Consequently, the effectiveness and superiority of the proposed method are carried out in a real-world NG gathering pipeline.
Intelligent Fault Diagnosis Method for Gearboxes Based on Deep Transfer Learning
Authors: Wu Zhenghao , Bai Huajun , Yan Hao , Zhan Xianbiao , Guo Chiming , Jia Xisheng
Published: December 2022

The complex operating environment of gearboxes and the easy interference of early fault feature information make fault identification difficult. This paper proposes a fault diagnosis method based on a combination of whale optimization algorithm (WOA), variational mode decomposition (VMD), and deep transfer learning. First, the VMD is optimized by using the WOA, and the minimum sample entropy is used as the fitness function to solve for the K value and penalty parameter α corresponding to the optimal decomposition of the VMD, and the correlation coefficient is used to reconstruct the signal. Second, the reconstructed signal after reducing noise is used to generate a two-dimensional image using the continuous wavelet transform method as the transfer learning target domain data. Finally, the AlexNet model is used as the transfer object, which is pretrained and fine-tuned with model parameters to make it suitable for early crack fault diagnosis in gearboxes. The experimental results show that the method proposed in this paper can effectively reduce the noise of gearbox vibration signals under a complex working environment, and the fault diagnosis method of using transfer learning is effective and achieves high accuracy of fault diagnosis.
Analysis of the Flow Field at the Tip of an Axial Flow Compressor during Rotating Stall Process Based on the POD Method
Authors: Wang Yueheng , Song Moru , Xin Jiali , Yang Bo
Published: December 2022

Rotating stalls are one of the most dangerous phenomena to be avoided in the designing and operating of axial flow compressors. An understanding of the evolution of the flow characteristics around the rotor tip region is important to study the process of stall development. In this paper, some critical characteristics of the stall-related structures, which could not be observed by the traditional analysis methods, are understood by using the proper orthogonal decomposition (POD) method. The detailed unsteady flow fields in a typical transonic axial flow compressor during the stall process are obtained by the validated numerical simulation. Thereafter, the proper orthogonal decomposition method, as a method for model reduction and decomposition, is adopted to extract the flow characteristics from the numerical results of the stall process. It is found that the flow characteristics during the stall process can be well decomposed by the POD method. The pre-stall POD results show that the important flow features can be extracted and revealed in the low-order modes, which are not obvious in the original flow field. When the stall cells are formed and developed, the flow characteristics are gradually determined by the modes, which are related to the features of the stall cells. When the compressor is operated under stable stall conditions, the low-order POD modes are composed of a series of harmonic modes, which are sinusoid-like in space and time with the frequency of the stall cell rotation.
Strain Rate Effect on Mode I Debonding Characterization of Adhesively Bonded Aluminum Joints
Authors: Khan Safdar Ali , Rahimian Koloor Seyed Saeid , King Jye Wong , Yidris Noorfaizal , Mohd Yusof Ab Aziz , Mohd Szali Januddi Mohd Al Fatihhi , Tamin Mohd Nasir , Johar Mahzan
Published: December 2022

In adhesive bonding, two different substrate materials are joined together, usually by forming chemical bonds. The adhesive can stick things together. The loading rate and deformation mode can easily change the mechanical properties of the adhesive material. Hence, a vital aim of the current study is to evaluate the strain rate effect on the damage response of adhesive joints for Mode I loading scenarios. The adherend material was aluminum AL6061-T6, and Araldite 2015 was the adherent material. This experiment for delamination had a prescribed adherend size of 200 mm × 25 mm × 3 mm and an adhesive thickness of 0.5 mm. In situations where the strain rate affects the failure mechanism, a displacement rate of 5, 50, or 500 mm/min is sufficient to attain the failure mechanism. A double cantilever beam (DCB) specimen was employed to construct the FE model geometry for simulation. A hybrid experimental–FE technique was utilized to extract the properties of the adhesive interface. FE simulation has proven to have an excellent correlation with the experimental findings.
Review of Methods for Diagnosing Faults in the Stators of BLDC Motors
Authors: Solís Ricardo , Torres Lizeth , Pérez Pablo
Published: December 2022

A brushless direct current (BLDC) motor is a type of permanent magnet machine that is highly efficient and powerful and requires occasional maintenance. Thanks to these fortunate characteristics, this type of motor has various applications in high-tech industries. However, since BLDC motors are often required to operate at high-speed rotations and under extreme conditions, temperature overshoots can appear during operation, provoking damage to the windings. The purpose of this review is to present the results of a recent investigation and recollection of different methods used for the diagnosis of electrical faults in the stator, such as turn-to-turn short circuits, coil-to-coil short circuits, phase-to-phase short circuits and phase open circuits. In particular, this review presents an analysis of the available diagnosis methods according to the type of fault, the method or technique used for the diagnosis, the evaluated physical variables and the context in which the methods were evaluated (in simulations or in experimental tests). Based on this analysis, the following classifications of diagnostic methods are proposed: signal-based, model-based and data-based methods. Then, the pros and cons of each method class are described and discussed.
Significant Wave Height Retrieval Using XGBoost from Polarimetric Gaofen-3 SAR and Feature Importance Analysis
Authors: Song Tianran , Yan Qiushuang , Fan Chenqing , Meng Junmin , Wu Yuqi , Zhang Jie
Published: December 2022

Empirical algorithms have become the mainstream of significant wave height (SWH) retrieval from synthetic aperture radar (SAR). But the plentiful features from multi-polarizations make the selection of input for the empirical model a problem. Therefore, the XGBoost models are developed and evaluated for SWH retrieval from polarimetric Gaofen-3 wave mode imagettes using the SAR features of different polarization combinations, and then the importance of each feature on the models is further discussed. The results show that the reliability of SWH retrieval models is independently confirmed based on the collocations of the SAR-buoy and SAR-altimeter. Moreover, the combined-polarization models achieve better performance than single-polarizations. In addition, the importance of different features to the different polarization models for SWH inversion is not the same. For example, the normalized radar cross section (NRCS), cutoff wavelength (λc), and incident angle (θ) have more decisive contributions to the models than other features, while peak wavelength (λp) and the peak direction (φ) have almost no contribution. Besides, NRCS of cross-polarization has a more substantial effect, and the λc of hybrid polarization has a stronger one than other polarization models.
Comparison of Novel Hybrid and Benchmark Machine Learning Algorithms to Predict Groundwater Potentiality: Case of a Drought-Prone Region of Medjerda Basin, Northern Tunisia
Authors: Trabelsi Fatma , Bel Hadj Ali Salsebil , Lee Saro
Published: December 2022

Water scarcity is a severe problem in Tunisia, particularly in the northern region crossed by the Medjerda River, where groundwater is a conjoint water resource that is increasingly exploited. The aim of this study is to delineate the groundwater potential zones (GWPZs) in the Lower Valley of the Medjerda basin by using single benchmark machine learning models based on artificial neural network (ANN), random forest (RF), and support vector regression (SVR), and by developing a novel hybrid method, NB-RF-SVR, to reach the highest accuracy of groundwater potential prediction. Each model produced a spatial groundwater potential map (GPM) with the input of 26 groundwater-related factors (GRF) selected by the frequency ratio model and 70% of the transmissivity training data. The models’ effectiveness was assessed using the AUC-ROC curve, sensitivity, specificity, MAE, and RMSE metric indicators. The validation findings revealed that all the models performed successfully for the GWPZ mapping, where the AUC values for the ANN, RF, SVR, and NB-RF-SVR models were estimated as 71%, 79%, 87%, and 92%, respectively. The relative importance of the GWPZs revealed that land use followed by geology and elevation were the most important factors. Finally, these outcomes can provide valuable information for decision makers to effectively manage groundwater in water-stressed regions.
Multi-Domain Fusion Graph Network for Semi-Supervised PolSAR Image Classification
Authors: Tang Rui , Pu Fangling , Yang Rui , Xu Zhaozhuo , Xu Xin
Published: December 2022

The expensive acquisition of labeled data limits the practical use of supervised learning on polarimetric synthetic aperture radar (PolSAR) image analysis. Semi-supervised learning has attracted considerable attention as it can utilize few labeled data and very many unlabeled data. The scattering response of PolSAR data is strongly spatial distribution dependent, which provides rich information about land-cover properties. In this paper, we propose a semi-supervised learning method named multi-domain fusion graph network (MDFGN) to explore the multi-domain fused features including spatial domain and feature domain. Three major factors strengthen the proposed method for PolSAR image analysis. Firstly, we propose a novel sample selection criterion to select reliable unlabeled data for training set expansion. Multi-domain fusion graph is proposed to improve the feature diversity by extending the sample selection from the feature domain to the spatial-feature fusion domain. In this way, the selecting accuracy is improved. By few labeled data, very many accurate unlabeled data are obtained. Secondly, multi-model triplet encoder is proposed to achieve superior feature extraction. Equipped with triplet loss, limited training samples are fully utilized. For expanding training samples with different patch sizes, multiple models are obtained for the fused classification result acquisition. Thirdly, multi-level fusion strategy is proposed to apply different image patch sizes for different expanded training data and obtain the fused classification result. The experiments are conducted on Radarsat-2 and AIRSAR images. With few labeled samples (about 0.003–0.007%), the overall accuracy of the proposed method ranges between 94.78% and 99.24%, which demonstrates the proposed method’s robustness and excellence.
Exploring the Role of Educational Human Capital and Green Finance in Total-Factor Energy Efficiency in the Context of Sustainable Development
Authors: Ma Wenxuan
Published: December 2022

The problem of lower total-factor energy efficiency (TFEE) has become a bottleneck for economic growth, and how to break this bottleneck and achieve high-quality development is one of the urgent issues to be solved nowadays. The study selects 30 provincial units in mainland China during 13 years, from 2008 to 2020; then adopts slack-based measure (SBM) method to measure the TFEE values of each province; and on this basis, finally explores the impact of educational human capital and green finance on regional TFEE in China; It concludes as follows: (1) The average value of TFEE in China is 0.776, which is at a lower level, and TFEE shows a gradual increase during the study period; the mean value decreases from east to west in descending order. (2) Educational human capital’s impact on the TFEE of the whole country and all regions is negative, and it does not show a significant U-shaped relationship; the effect of eastern region is the smallest; green finance’s impact on TFEE shows a U-shaped relationship, except in eastern regions, where it is not significant; and the coefficient of the central region is stronger. (3) Environmental regulation’s impact on TFEE show a U-shaped relationship in all regions; science and technology investment can improve TFEE all regions; and in the eastern region, it is most significant. Industrial structure is positively correlated with TFEE in all regions, and it has the most obvious effect on the improvement of TFEE in the central region; economic development can promote TFEE in all regions. This research has important theoretical implications for achieving regional TFEE improvement.
Structural Reform, Technological Progress and Total Factor Productivity in Manufacturing
Authors: Han Dechao
Published: December 2022

Beneficial institutional environments help to improve TFP in manufacturing. However, it is unclear whether China’s structural reform has led to improvements in TFP in the manufacturing industry. In this study, Sys-GMM was employed to assess the relationships between structural reform, technological progress and manufacturing TFP using panel data from provincial-level administrative regions in China from 2010 to 2020. The results showed the following: (1) Structural reform induced a spiral-shaped upward trend of TFP by affecting the technological progress levels of enterprises in China, which was also enhanced by improvements in regional technology levels. (2) The impact of market-oriented reform on industrial TFP was similar to that of entire structural reform; however, innovation environments did not significantly impact industrial TFP, technological progress had no regulatory effect and although the reform and the supply of public services could significantly promote improvements in industrial TFP, technological progress also exhibited no significant regulatory effect on these improvements. (3) The flow of technology and labor significantly, positively correlated with industrial TFP, while resource idleness had a salient inhibitory effect. In addition, enhancement of the disclosed comparative advantage, as well as further opening and expansion of operation scales of the manufacturing industry, could improve industrial TFP even more.
Case Study on Dynamic Identification of Overburden Fracture and Strong Mine Pressure Mechanism of Isolated Working Face Based on Microseismic Clustering
Authors: Chen Yiqi , Liu Changyou , Liu Jinrong , Yang Peiju , Lu Shuo
Published: December 2022

Strong mine pressure has a great impact upon the safety production of coal mines. Microseismic information provides a more advanced technical means for overburden fracture dynamic identification and mine pressure mechanism research, since it contains rich information on rock fracture sources. In this study, the isolated LW8102 working face in Tongxin Mine was investigated in order to propose a spatio-temporal microseismic event data analysis method based on the k-means clustering algorithm. This algorithm can handle dynamic identification of overburden fractures constrained by spatiotemporally discrete distributions of microseismic events. This provided the dynamic extension process and the fracture distribution pattern of the overburden: eight fracture extensions were formed in the overburden. In each extension, vertical fractures connected the low and high rock layers in the LW8102 and LW8103 goafs, and through fractures connected the LW8102 and LW8103 goafs in their high, middle, and low levels. Some extensions had fractures that were connected to form a closed loop structure. In the vertical fracture, there was a tendency for one or two layers of the stratum to fail first, and then extend to one or both sides. The process of through and vertical fracture propagation followed a certain temporal sequence, reflected primarily in two forms: firstly, as the vertical fracture extended to a certain layer, it provided the initial rupture space for through fracture spreading; secondly, the through fracture first broke, and then extended to the vertical fracture until it intersected with the vertical fracture or provided the initial rupture space for the expansion of the vertical fracture. By matching the overburden fracture to the mine pressure that responded to the support resistance, we analyzed the mechanism of mine pressure at the working face. Through fracture at the high level was found to be the primary cause of the occurrence of mining pressure. It was precisely placed that the formation of multiple adjacent high through fractures 110 m from the floor, triggering simultaneous instability motion of the lower multi-layer level rock; this was the main reason for the phenomenon of strong mine pressure at the working face. Meanwhile, high through fracture at 80 m from the floor was the main reason for the phenomenon of large mine pressure at the working face.
A Multiobjective Evolutionary Approach for Solving the Multi-Area Dynamic Economic Emission Dispatch Problem Considering Reliability Concerns
Authors: Lotfi Hossein
Published: December 2022

Economic dispatch (ED) problems, especially in multi-area power networks, have been challenging concerns for power system operators for several decades. In this paper, we introduce a novel approach for solving the multiobjective multi-area dynamic ED (MADED) problem in the presence of practical constraints such as valve-point effect (VPE), prohibited operating zone (POZ), multi-fuel operation (MFO), and ramp rate (RR) limitations. Different objective functions including energy not supplied (ENS), generation costs, and emissions are investigated. The reliability objective, which has been less studied in economic dispatch area, distinguishes the proposed study from other studies. A compromise has been made from economic and reliability points of view. The MADED problem in the power system is inherently a complex and nonlinear problem, considering the operational constraint increments and the intricacy of the problem. Hence, the modified grasshopper optimization (MGO) algorithm based on a chaos mechanism is presented to prevent being trapped in local optima. The proposed method is tested on two systems including a 10 unit, 3-zone test system and a 40-unit 3-zone test system, and then, the outcomes are compared with those of other evolutionary techniques such as gray wolf optimization (GWO) and modified honey bee mating optimization (MHBMO). The simulation results demonstrate that the suggested strategy is successful in resolving both single-objective and multiobjective MADED problems.
Enhancing Household Welfare through Perennial Crop Production in Northern Ghana
Authors: Danso-Abbeam Gideon , Amin Khama Mohammed , Ogundeji Abiodun A.
Published: December 2022

As Ghana seeks to diversify its agricultural export commodity trade away from its over-reliance on cocoa, empirical evidence is critical to inform policy direction on the implementation of programs to promote such an agenda. The objective of the study was to determine whether farmers who cultivate perennial crops as their primary source of livelihood have better welfare gains than farmers who cultivate perennial crops. The study used cross-sectional data collected from 386 farming households in the northern region of Ghana. The propensity score-matching technique augmented with a control function estimator was employed in order to account for self-selection biases in household characteristics that could invalidate the quality and magnitude of the estimates. Factors identified to positively and significantly influence households’ decision to cultivate perennial crops include number of male adults in a household, farm size, membership of farmer groups, value of agricultural credit, and distance from homestead to the farm. The empirical evidence further indicated that farmers who grow perennial crops have higher welfare gains in terms of consumption expenditure per capita, household income per capita, and farm income per hectare than farmers who grow annual crops as their primary source of income. On the other hand, annual crop farmers have a wider spread of income (income diversification) than perennial crop farmers. Sensitizing farming households to engage in perennial crop production, at the very least, as an alternative source of livelihood, will aid in the fight against poverty and food insecurity, as well as improve Ghana’s macroeconomic balances through agricultural export revenue.
Research on Coupling Coordination of China’s New-Type Urbanization and Urban Resilience—Taking Yangtze River Economic Belt as an Example
Authors: Liu Nina , Wang Shuqi , Su Fei , Ye Jun
Published: December 2022

The coupled and coordinated development of urban resilience and new urbanization is an important guarantee for the realization of urban security and sustainable development. This paper first constructs an evaluation index of urban resilience and new urbanization and uses the entropy method to clarify the weights. Second, the coupling coordination degree model is used to measure the spatiotemporal differentiation characteristics of the coupling coordinated development of urban resilience and new urbanization in the Yangtze River Economic Belt from 2005 to 2019. The key influencing factors of the coupling coordination are analyzed using geodetectors. The results show the following. (1) The urban resilience of the Yangtze River Economic Belt has continued to improve, showing a stepwise distribution pattern of “high in the east and low in the west” in space. The overall development of new urbanization is at a medium–high level, with high levels concentrated in the eastern coastal cities. (2) The degree of spatial coupling and coordination between urban resilience and new urbanization is increasing year by year, and there is significant spatial heterogeneity, showing the pattern of “high in the east and low in the west, high in the center and low in the surrounding areas”, and the type of lag is mostly urban resilience lag in new urbanization. (3) Endogenous power, external power, government power and market power interact to jointly promote the development of coupling coordination. The comprehensive effect of government power and other driving forces is the key mechanism for improving spatial coupling coordination.
Effects of Rotational Tillage on Soil Physicochemical Properties and Crop Yield in a Rice–Wheat Double Cropping Area
Authors: Zhang Yin-Ping , Li Xin , He Hao-Jie , Zhou Hua , Geng Duan-Yang , Zhang Yu-Zi
Published: December 2022

This paper aims to explore issues related to destruction of soil nutrients and structure in a rice-wheat double-cropping area caused by over-tillage prior to rice cultivation. A three-year cycle of rotation tillage pattern (RT), consisting of “no-tillage–no-tillage–plough”, with a straw-returning and direct rice-seeding technology, was designed and tested, and was compared with continuous no-tillage pattern (CN) and conventional ploughing & rotary tillage (PR). The soil rotation experiment in the rice-wheat double-cropping region is located on the southeastern coast of Shandong Province, with a warm, temperate, humid monsoon climate and paddy soil type. Comparison experiments were conducted on the three farming patterns over a period of 3 years, continuously measuring soil physical and chemical properties and crop yields. The results showed that under the same straw-returning conditions, RT significantly increased soil macroaggregates content and enhanced their stability within 0~30 cm (p < 0.05). RT significantly reduced the bulk density of 0~30 cm soil to below 1.5 g/cm3, which was beneficial to crop root growth (p < 0.05). Meanwhile, RT significantly increased the contents of soil organic carbon, total nitrogen, and available phosphorus, and the nutrients are evenly distributed in 0~30 cm layer (p < 0.05). Another result was that the RT significantly increased the rice panicle length, grains number per panicle, and thousand-grain weigh. The crop yield was not significantly different from that of PR, but significantly higher than that of CN (p < 0.05). At the same time, cultivation measures prior to rice cultivation had some after-effects on wheat; the RT significantly increased the average tillers, effective panicle number, effective panicle grain number, and thousand-seed weight of wheat; and the wheat yields were 10.5% and 13.3% higher than that of CN and PR, respectively. This study provides a theoretical reference for improving tillage patterns in rice-wheat double-cropping areas.
A Crack Width Measurement Method of UAV Images Using High-Resolution Algorithms
Authors: Yoon Jonghyeon , Shin Hyunkyu , Song Mihwa , Gil Heungbae , Lee Sanghyo
Published: December 2022

The need for maintenance is increasing due to the aging of facilities. In this study, we proposed a crack width measurement method for images collected at safe distances using UAVs (Unmanned Aerial Vehicles). It is a method of measuring the widths of cracks using a high-resolution (VDSR) algorithm, which measures by increasing the resolution of images taken at 3 m intervals on the wall where cracks exist. In addition, the crack width measurement value was compared with a general photographed image and a high-resolution conversion image. As a result, it was confirmed that the crack width measurement of the image to which the high resolution was applied was similar to the actual measured value. These results can help improve the practical applicability of UAVs for facility safety inspections by overcoming the limits of camera resolution and distances between UAVs and facilities introduced in the facility safety inspection. However, more detailed image resolution is required to quantitatively measure the crack width; we intend to improve this through additional studies.
Performing Group-Based Physical Activity (Gbpa) in the Work-Place: Survey and Sociological Considerations of the “Happy Bones” Project
Authors: Lenzi Francesca Romana , Tranchita Eliana , Grazioli Elisa , Cerulli Claudia , Esposito Vincenzo , Coppola Giuseppe , Moretti Elisa , Mauri Caterina , Minganti Carlo , Parisi Attilio
Published: December 2022

The goal of the following work was to identify the effects, positive or negative, of performing group-based physical activity (GBPA) in the workplace. In addition, the scope of the present research was to investigate some social and relational aspects of medical origin associated with the Happy Bones project. The sample consisted of 28 women between 47 and 67 years old, employees of the University of Rome “Foro Italico”, in menopause, and inactive. The explorative nature of the investigation and the multidimensional aspect of the variables suggested the adoption of a qualitative method. Even though the survey did not fulfil the minimum standards of representativeness, interview analysis showed a positive trend in joining physical activity in the workplace, as shown by the good compliance of the participants with the proposed workplace training protocol. Personal motivation linked to the project itself or to the corresponding activity existed albeit to a secondary extent; the unifying element of the group existed regardless of the project and was due to the home institution, hence to the workplace.
Crop Type Prediction: A Statistical and Machine Learning Approach
Authors: Bhuyan Bikram Pratim , Tomar Ravi , Singh T. P. , Cherif Amar Ramdane
Published: December 2022

Farmers’ ability to accurately anticipate crop type is critical to global food production and sustainable smart cities since timely decisions on imports and exports, based on precise forecasts, are crucial to the country’s food security. In India, agriculture and allied sectors constitute the country’s primary source of revenue. Seventy percent of the country’s rural residents are small or marginal agriculture producers. Cereal crops such as rice, wheat, and other pulses make up the bulk of India’s food supply. Regarding cultivation, climate and soil conditions play a vital role. Information is of utmost need in predicting which crop is best suited given the soil and climate. This paper provides a statistical look at the features and indicates the best crop type on the given features in an Indian smart city context. Machine learning algorithms like k-NN, SVM, RF, and GB trees are examined for crop-type prediction. Building an accurate crop forecast system required high accuracy, and the GB tree technique provided that. It outperforms all the classification algorithms with an accuracy of 99.11% and an F1-score of 99.20%.
Brazilian Biodiversity as a Source of Power and Sustainable Development: A Neglected Opportunity
Authors: Ellwanger Joel Henrique , Nobre Carlos Afonso , Chies José Artur Bogo
Published: December 2022

Six terrestrial biomes and a huge coastline make Brazil one of the most biodiverse countries in the world. However, the potential of Brazilian biodiversity as a valuable and sustainable source of wealth and development is still neglected. In order to reverse this scenario, the country needs to recognize and assume the power of its biodiversity, focusing on (I) industry, science and technology, (II) biological conservation and maintenance of ecosystem services, considering reverberations on agriculture and public health, and (III) ecotourism, conservation and sustainable development of local populations. The joint action of the Brazilian population and scientific community is needed to achieve these goals, which must be translated into the election of politicians committed to sustainable development and an increase in research and technology based on Brazilian biodiversity. Additional reasons for preserving Brazilian biodiversity (e.g., intrinsic, cultural, and ethical values) are also addressed in this article. Finally, we argue that Brazil should recover its global leadership on the environmental agenda and assume its biological diversity as a source of Soft Power, as well as develop its neglected capacity in the field of the sustainable bio-based economy (bioeconomy). In brief, Brazil needs to recognize and embrace the power of its biodiversity.
The Obligation of EIA in the International Jurisprudence and Its Impact on the BBNJ Negotiations
Authors: Song Yan
Published: December 2022

Environmental impact assessment (EIA) has been widely recognized as a crucial instrument for sound decision-making that will promote environmental conservation and sustainable development. International jurisprudence has clarified the obligation of EIA under customary international law, especially concerning its legal status, threshold standards, and procedural requirements, as well as the issue of State responsibility. As suggested by this article, international tribunals tend to adopt a procedural-oriented and State-based approach regarding the obligation of EIA, leaving more discretion to the States pursuing the proposed activities. This approach is insufficient to realize the role of EIA in fostering sound decision-making. As for the BBNJ negotiations, in light of the legal status of the Area in international law and the established rules governing the issues of EIA, especially the three Regulations and Recommendations adopted by ISA, the future implementation agreement should reinforce international regulations regarding the substance and implementation of EIA obligations.