bluuebunny/crossref_metadata_2025 huggingface dataset:
The trend of groundwater recharge in the secondary perched reaches of the Yellow River in the past 50 years
Authors: Zhang Min , Ping Jianhua , Mei Xuemei , Leng Wei , Li He , Zhao Jichang , Liu Jiaqi
Published: December 2023

Precipitation infiltrates into the soil or river and then percolates downward through the deeper mineral soil to the groundwater. Understanding the interactions between surface water and groundwater in the river ecosystem is crucial for supporting decision-making in eco-construction and the efficient use of water resources. In our study, the secondary perched reach of the lower Yellow River was taken as the research area. The trend analysis and correlation relationship were evaluated using the M–K significance test and gray correlation; furthermore, the groundwater recharge was quantified by Darcy‘s law and the water balance method based on 50 years of hydrological data. The results showed that 1) from 1972 to 2020, the runoff and water level of the Huayuankou hydrological station and the Jiahetan hydrological station showed a significant downward trend. 2) The calculation of the gray correlation degree method shows that the groundwater level is mainly affected by the Yellow River. The river water and groundwater levels show a significant downward trend using the M–K significance test. 3) The unit width recharge values of the secondary perched river to the groundwater in the dry year were calculated to be 566.79 and 374.13 m3/m·d, using Darcy‘s law and the water balance method, respectively, indicating that the results of the two methods are basically the same. Our findings highlight the storage capacity of groundwater and can provide support for regulation and sustainable management of water resources in the ecosystem.
Does China’s emission trading scheme promote industry-level green innovation: evidence from Guangdong pilot market
Authors: Zhou Kaiguo , Guan Zihuan , Lu Yunzhi
Published: December 2023

Green innovation has been the crucial and fundamental channel for efficient emission reduction and high-quality realization of the “Dual Carbon” goals. This paper provides novel evidence for the industry-level effect of Emission Trading Scheme (ETS) on green innovation. Specifically, adopting the supply chain Stackelberg model and the multi-period DID model, we demonstrate both theoretically and empirically that the ETS has an overall significant promotion effect on green innovation both in compliance and non-compliance industries. Surprisingly, the promotion effect in non-compliance industries will be stronger, forced by the costs pass-through from up-stream compliance industries. Furthermore, we also find that the carbon price level can amplify the positive effect of the ETS on industry green innovation in the short run, while the price volatility weakens the effect of the ETS in the long run. Our findings shed light on the inherent effects of ETS on green innovation and suggest that policymakers should stabilize the carbon prices so as to encourage green innovation.
Immune checkpoint inhibitors as potential therapy for reverting T-cell exhaustion and reverting HIV latency in people living with HIV
Authors: Benito José M. , Restrepo Clara , García-Foncillas Jesús , Rallón Norma
Published: December 2023

The immune system of people living with HIV (PLWH) is persistently exposed to antigens leading to systemic inflammation despite combination antiretroviral treatment (cART). This inflammatory milieu promotes T-cell activation and exhaustion. Furthermore, it produces diminished effector functions including loss of cytokine production, cytotoxicity, and proliferation, leading to disease progression. Exhausted T cells show overexpression of immune checkpoint molecules (ICs) on the cell surface, including programmed cell death protein 1 (PD-1), cytotoxic T-lymphocyte-associated antigen-4 (CTLA-4), T-cell immunoglobulin and mucin-domain containing-3 (TIM-3), T-cell immunoglobulin and immunoreceptor tyrosine-based inhibitory motif domain (TIGIT), and lymphocyte activation gene-3 (LAG-3). The ICs also play a crucial role in T-cell exhaustion by reducing the immune response to cancer antigens. Immunotherapy based on immune checkpoint inhibitors (ICIs) has changed the management of a diversity of cancers. Additionally, the interest in exploring this approach in the setting of HIV infection has increased, including AIDS-defining cancers and non-AIDS-defining cancers in PLWH. To date, research on this topic suggests that ICI-based therapies in PLWH could be a safe and effective approach. In this review, we provide an overview of the current literature on the potential role of ICI-based immunotherapy not only in cancer remission in PLWH but also as a therapeutic intervention to restore immune response against HIV, revert HIV latency, and attain a functional cure for HIV infection.
Multifactor assessment of ovarian cancer reveals immunologically interpretable molecular subtypes with distinct prognoses
Authors: Guo Yaping , Li Siyu , Li Chentan , Wang Li , Ning Wanshan
Published: December 2023

Background

Ovarian cancer (OC) is a highly heterogeneous and malignant gynecological cancer, thereby leading to poor clinical outcomes. The study aims to identify and characterize clinically relevant subtypes in OC and develop a diagnostic model that can precisely stratify OC patients, providing more diagnostic clues for OC patients to access focused therapeutic and preventative strategies.

Methods

Gene expression datasets of OC were retrieved from TCGA and GEO databases. To evaluate immune cell infiltration, the ESTIMATE algorithm was applied. A univariate Cox analysis and the two-sided log-rank test were used to screen OC risk factors. We adopted the ConsensusClusterPlus algorithm to determine OC subtypes. Enrichment analysis based on KEGG and GO was performed to determine enriched pathways of signature genes for each subtype. The machine learning algorithm, support vector machine (SVM) was used to select the feature gene and develop a diagnostic model. A ROC curve was depicted to evaluate the model performance.

Results

A total of 1,273 survival-related genes (SRGs) were firstly determined and used to clarify OC samples into different subtypes based on their different molecular pattern. SRGs were successfully stratified in OC patients into three robust subtypes, designated S-I (Immunoreactive and DNA Damage repair), S-II (Mixed), and S-III (Proliferative and Invasive). S-I had more favorable OS and DFS, whereas S-III had the worst prognosis and was enriched with OC patients at advanced stages. Meanwhile, comprehensive functional analysis highlighted differences in biological pathways: genes associated with immune function and DNA damage repair including CXCL9, CXCL10, CXCL11, APEX, APEX2, and RBX1 were enriched in S-I; S-II combined multiple gene signatures including genes associated with metabolism and transcription; and the gene signature of S-III was extensively involved in pathways reflecting malignancies, including many core kinases and transcription factors involved in cancer such as CDK6, ERBB2, JAK1, DAPK1, FOXO1, and RXRA. The SVM model showed superior diagnostic performance with AUC values of 0.922 and 0.901, respectively. Furthermore, a new dataset of the independent cohort could be automatically analyzed by this innovative pipeline and yield similar results.

Conclusion

This study exploited an innovative approach to construct previously unexplored robust subtypes significantly related to different clinical and molecular features for OC and a diagnostic model using SVM to aid in clinical diagnosis and treatment. This investigation also illustrated the importance of targeting innate immune suppression together with DNA damage in OC, offering novel insights for further experimental exploration and clinical trial.
Bacteremia caused by Comamonas kerstersii in a patient with acute perforated appendicitis and localized peritonitis: case report and literature review
Authors: Zhang Yingmiao , Li Kun , Zhan Yu , Shi Lifeng , Zeng Yi , Wang Hui , Lu Zhongxin
Published: December 2023

Comamonas kerstersii (C. kerstersii) is a Gram-negative bacterium that was initially thought to be non-pathogenic to humans and is abundant in the environment. In recent years, with the availability of matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) that enable fast and accurate bacterial identification, there have been increasing number of reports of human infections caused by C. kerstersii, indicating that this organism has emerged as human pathogen. In fact, most clinical isolates of C. kerstersii are recovered from peritoneal liquid, and bacteremia has been infrequently reported. Here, we report a case of bacteremia caused by C. kerstersii in a 28-year-old male patient with acute perforated appendicitis and localized peritonitis and present a comprehensive review of C. kerstersii infections in pathogenic diagnosis and clinical treatment as well as prognosis, thus providing a better understanding of C. kerstersii-related infections.
Quantifying neptunium oxidation states in nitric acid through spectroelectrochemistry and chemometrics
Authors: Sadergaski Luke R. , Andrews Hunter B. , Gilson Sara E. , Parkison Adam J.
Published: December 2023

Controlled-potential in situ thin-layer spectropotentiometry was leveraged to generate visible/near-infrared (VIS/NIR) absorption spectral data sets for the development of chemometric models to quantify Np(III/IV/V/VI) oxidation states in HNO3. This technology would be valuable in laboratory studies and when monitoring process solutions to guide feed adjustments for radiochemical separations—the performance of which depends on oxidation state. This approach successfully isolated and stabilized Np species in pure (∼99%) oxidation states without compromising solution optical properties. Multivariate curve resolution–alternating least squares models were evaluated to resolve spectral and component concentrations from a scan that sequentially produced Np(VI), Np(V), Np(IV), and Np(III) spectra with mixtures of two valences at a time. Although it provided a useful approximation, the method was not able to quantitively resolve each component likely because of rotational ambiguity. Additionally, partial least squares regression models were built from artificial and electrochemically generated VIS/NIR spectral training sets to study the effect of interionic interactions on spectral characteristics. Models built with true Bi-chemical mixtures of coexisting Np oxidation states and spectra generated from additive combinations of pure end points had similar prediction performance. This methodology can be used to directly quantify Np concentration and the ratio of Np oxidation states and other actinides in remote settings such as hot cells.
Preclinical evidence for anaplastic lymphoma kinase inhibitors as novel therapeutic treatments for cholangiocarcinoma
Authors: Myint Kyaw Zwar , Sueca-Comes Mireia , Collier Pamela , Balasubramanian Brinda , Venkatraman Simran , Gordan John , Zaitoun Abed M. , Mukherjee Abhik , Arora Arvind , Larbcharoensub Noppadol , Suriyonplengsaeng Chinnawut , Wongprasert Kanokpan , Janvilisri Tavan , Gomez Dhanny , Grabowska Anna M. , Tohtong Rutaiwan , Bates David O. , Yacqub-Usman Kiren
Published: December 2023

Introduction

Bile duct cancer (cholangiocarcinoma, CCA) has a poor prognosis for patients, and despite recent advances in targeted therapies for other cancer types, it is still treated with standard chemotherapy. Anaplastic lymphoma kinase (ALK) has been shown to be a primary driver of disease progression in lung cancer, and ALK inhibitors are effective therapeutics in aberrant ALK-expressing tumors. Aberrant ALK expression has been documented in CCA, but the use of ALK inhibitors has not been investigated. Using CCA cell lines and close-to-patient primary cholangiocarcinoma cells, we investigated the potential for ALK inhibitors in CCA.

Methods

ALK, cMET, and ROS1 expression was determined in CCA patient tissue by immunohistochemistry and digital droplet polymerase chain reaction, and that in cell lines was determined by immunoblot and immunofluorescence. The effect on cell viability and mechanism of action of ALK, cMet, and ROS1 inhibitors was determined in CCA cell lines. To determine whether ceritinib could affect primary CCA cells, tissue was taken from four patients with biliary tract cancer, without ALK rearrangement, mutation, or overexpression, and grown in three-dimensional tumor growth assays in the presence or absence of humanized mesenchymal cells.

Results

ALK and cMet but not ROS were both upregulated in CCA tissues and cell lines. Cell survival was inhibited by crizotinib, a c-met/ALK/ROS inhibitor. To determine the mechanism of this effect, we tested c-Met-specific and ALK/ROS-specific inhibitors, capmatinib and ceritinib, respectively. Whereas capmatinib did not affect cell survival, ceritinib dose-dependently inhibited survival in all cell lines, with IC50 ranging from 1 to 9 µM and co-treatments with gemcitabine and cisplatin further sensitized cells, with IC50 ranging from IC50 0.60 to 2.32 µM. Ceritinib did not inhibit cMet phosphorylation but did inhibit ALK phosphorylation. ALK was not mutated in any of these cell lines. Only ceritinib inhibited 3D growth of all four patient samples below mean peak serum concentration, in the presence and absence of mesenchymal cells, whereas crizotinib and capmatinib failed to do this. Ceritinib appeared to exert its effect more through autophagy than apoptosis.

Discussion

These results indicate that ceritinib or other ALK/ROS inhibitors could be therapeutically useful in cholangiocarcinoma even in the absence of aberrant ALK/ROS1 expression.
Correlation between long non-coding RNA MAFG-AS1 and cancer prognosis: a meta-analysis
Authors: Lin Guangyao , Liu Huicong , Lin Jingyu , Liu Xiyu , Xu Lianwei
Published: December 2023

Background

MAF transcription factor G antisense RNA 1 (MAFG-AS1), a novel long non-coding RNA discovered recently, was proved to be useful in predicting malignancy prognosis. Nevertheless, its association with cancer prognosis has been inconsistent. Therefore, this meta-analysis aimed to explore the clinicopathological and prognostic significance of MAFG-AS1 in diverse carcinomas.

Methods

Studies focused on MAFG-AS1 expression as a prognostic role in cancers were thoroughly searched in six electronic databases. The value of MAFG-AS1 in malignancies was assessed by hazard ratios (HRs) or odds ratios (ORs). Additionally, the GEPIA database was utilized to further strengthen our conclusion.

Results

A total of 15 studies involving 1187 cases and nine types of cancers were recruited into this meta-analysis. High MAFG-AS1 expression was significantly related to advanced tumor stage (OR = 0.52, 95%CI [0.39, 0.69], P < 0.00001), earlier lymph node metastasis (OR = 3.62, 95%CI [2.19, 5.99], P < 0.00001), worse tumor differentiation (OR = 0.64, 95%CI [0.43, 0.95], P = 0.03), and poor overall survival (HR = 1.94, 95%CI [1.72, 2.19], P < 0.00001). No significant heterogeneity and publication bias was detected across studies. Meanwhile, MAFG-AS1 was significantly elevated in ten kinds of cancers based on the validation of the GEPIA database.

Conclusion

The results of this meta-analysis indicated that high MAFG-AS1 expression is dramatically correlated with unfavorable prognosis in cancers. MAFG-AS1 may be served as a promising biomarker for malignancies.
Antinociceptive and antiinflammatory activities of crude leave extract and solvent fractions of Commelina latifolia Hochst. ex C.B.Clarke (Commelinaceae) leaves in murine model
Authors: Tadege Getnet , Sirak Betelhem , Abebe Dehnnet , Nureye Dejen
Published: December 2023

Ethnopharmacological relevance: In the past, Ethiopian traditional medicine employed the leaves of the native Commelina latifolia Hochst. ex C.B. Clarke plant to treat wounds, pain, and malaria.

Aim of the study: The crude extract and solvent fractions of C. latifolia Hochst. ex C.B. Clarke leaves were examined in the present investigation to determine their ability to have an antiinflammatory effect and provide an antinociceptive effect in animal models.

Materials and methods: The leaves of C. latifolia were extracted with 80% methanol, and the CL crude extract was further fractionated with chloroform, pure methanol, and distilled water. The carrageenan-induced paw edema model was used to test the extracts’ ability to reduce inflammation. The hotplate model and the acetic acid-induced writhing test on rodents were used to test the extracts’ potential antinociceptive effect to reduce pain.

Results: Inflammation was decreased by 64.59% with CL crude extract (400 mg/kg); 56.34% (400 mg/kg) of methanol fraction, 64.59% of aqueous fraction (400 mg/kg), and 38.27% of chloroform fraction in the carrageenan-induced inflammatory model. All extracts demonstrated a considerable lengthening of the nociception reaction time in the hot plate test, with a maximum antinociceptive effect of 78.98% (crude extract) and 71.65% (solvent fractions). At a dosage of 400 mg/kg, the natural C. latifolia crude extract and aqueous fraction demonstrated considerable antinociceptive effects against acetylsalicylic acid (ASA) during the writhing test (48.83% and 45.37than%, respectively). The current findings support Ethiopia’s traditional user’s assertions that the herb can alleviate inflammation and pain.
Metabolic patterns of sweat-extracellular vesicles during exercise and recovery states using clinical grade patches
Authors: Ali Nsrein , Rahat Syeda Tayyiba , Mäkelä Mira , Nasserinejad Maryam , Jaako Tommi , Kinnunen Matti , Schroderus Jyrki , Tulppo Mikko , Nieminen Anni I. , Vainio Seppo
Published: December 2023

Background: Metabolite-based sensors are attractive and highly valued for monitoring physiological parameters during rest and/or during physical activities. Owing to their molecular composition consisting of nucleic acids, proteins, and metabolites, extracellular vesicles (EVs) have become acknowledged as a novel tool for disease diagnosis. However, the evidence for sweat related EVs delivering information of physical and recovery states remains to be addressed.

Methods: Taking advantage of our recently published methodology allowing the enrichment and isolation of sweat EVs from clinical patches, we investigated the metabolic load of sweat EVs in healthy participants exposed to exercise test or recovery condition. -Ten healthy volunteers (-three females and -seven males) were recruited to participate in this study. During exercise test and recovery condition, clinical patches were attached to participants’ skin, on their back. Following exercise test or recovery condition, the patches were carefully removed and proceed for sweat EVs isolation. To explore the metabolic composition of sweat EVs, a targeted global metabolomics profiling of 41 metabolites was performed.

Results: Our results identified seventeen metabolites in sweat EVs. These are associated with amino acids, glutamate, glutathione, fatty acids, creatine, and glycolysis pathways. Furthermore, when comparing the metabolites’ levels in sweat EVs isolated during exercise to the metabolite levels in sweat EVs collected after recovery, our findings revealed a distinct metabolic profiling of sweat EVs. Furthermore, the level of these metabolites, mainly myristate, may reflect an inverse correlation with blood glucose, heart rate, and respiratory rate levels.

Conclusion: Our data demonstrated that sweat EVs can be purified using routinely used clinical patches during physical activity, setting the foundations for larger-scale clinical cohort work. Furthermore, the metabolites identified in sweat EVs also offer a realistic means to identify relevant sport performance biomarkers. This study thus provides proof-of-concept towards a novel methodology that will focus on the use of sweat EVs and their metabolic composition as a non-invasive approach for developing the next-generation of sport wearable sensors.
OsDWARF10, transcriptionally repressed by OsSPL3, regulates the nutritional metabolism of polished rice
Authors: Li Kang , Cheng Yan , Fang Chuanying
Published: December 2023

Strigolactone (SL) plays essential roles in plant development and the metabolism of rice leaves. However, the impact of SL on the accumulation of nutritional metabolites in polished rice, as well as the transcription factors directly involved in SL synthesis, remains elusive. In this study, we performed a metabolome analysis on polished rice samples from mutants of an SL biosynthetic gene, OsDWARF10 (OsD10). Compared with those in the wild type plants, primary and secondary metabolites exhibited a series of alterations in the d10 mutants. Notably, the d10 mutants showed a substantial increase in the amino acids and vitamins content. Through a yeast one-hybridization screening assay, we identified OsSPL3 as a transcription factor that binds to the OsD10 promoter, thereby inhibiting OsD10 transcription in vivo and in vitro. Furthermore, we conducted a metabolic profiling analysis in polished rice from plants that overexpressed OsSPL3 and observed enhanced levels of amino acids and vitamins. This study identified a novel transcriptional repressor of the SL biosynthetic gene and elucidated the regulatory roles of OsSPL3 and OsD10 on the accumulation of nutritional metabolites in polished rice.
The cross-race effect in automatic facial expression recognition violates measurement invariance
Authors: Li Yen-Ting , Yeh Su-Ling , Huang Tsung-Ren
Published: December 2023

Emotion has been a subject undergoing intensive research in psychology and cognitive neuroscience over several decades. Recently, more and more studies of emotion have adopted automatic rather than manual methods of facial emotion recognition to analyze images or videos of human faces. Compared to manual methods, these computer-vision-based, automatic methods can help objectively and rapidly analyze a large amount of data. These automatic methods have also been validated and believed to be accurate in their judgments. However, these automatic methods often rely on statistical learning models (e.g., deep neural networks), which are intrinsically inductive and thus suffer from problems of induction. Specifically, the models that were trained primarily on Western faces may not generalize well to accurately judge Eastern faces, which can then jeopardize the measurement invariance of emotions in cross-cultural studies. To demonstrate such a possibility, the present study carries out a cross-racial validation of two popular facial emotion recognition systems—FaceReader and DeepFace—using two Western and two Eastern face datasets. Although both systems could achieve overall high accuracies in the judgments of emotion category on the Western datasets, they performed relatively poorly on the Eastern datasets, especially in recognition of negative emotions. While these results caution the use of these automatic methods of emotion recognition on non-Western faces, the results also suggest that the measurements of happiness outputted by these automatic methods are accurate and invariant across races and hence can still be utilized for cross-cultural studies of positive psychology.
Urban digital economy, environmental pollution, and resident’s health–empirical evidence from China
Authors: Zhu Chen , Wang Zekai , Sun Bin , Yue Yuanyuan
Published: December 2023

In light of China’s rapid advancement in the digital economy and the implementation of the “Healthy China” initiative, it is crucial to assess the impact of the digital economy on residents’ health. This study analyzes data from the 2012, 2014, and 2016 China Labor Force Dynamics Survey (CLDS) to evaluate the health of residents using both subjective and objective criteria. Furthermore, it calculates the digital economy development index for Chinese cities and investigates its influence on the subjective and objective health of residents, along with the underlying mechanisms. The empirical results reveal a U-shaped pattern in the effect of the digital economy on health levels, initially detrimental but subsequently beneficial. The analysis of mechanisms shows that the digital economy’s development initially increases and then decreases environmental pollution, impacting health through environmental changes. Additionally, the study finds variations in this impact based on age and urban–rural differences, with more pronounced effects on rural and older adult populations, who also experience the U-shaped curve’s turning point more rapidly. These findings highlight the necessity of advancing digital economy infrastructure to positively influence environmental quality and improve public health. The study emphasizes the urgent need for policymakers to invest in digital infrastructure to foster a sustainable and healthy future. This requires a holistic approach to development, focusing on both urban and rural areas, to promote inclusive growth and reduce the digital divide.
Assessment of mortality risks due to a strong cold spell in 2022 in China
Authors: Wang Wanci , Ma Yuxia , Qin Pengpeng , Liu Zongrui , Zhao Yuhan , Jiao Haoran
Published: December 2023

Background

With the intensification of global climate warming, extreme low temperature events such as cold spells have become an increasingly significant threat to public health. Few studies have examined the relationship between cold spells and mortality in multiple Chinese provinces.

Methods

We employed health impact functions for temperature and mortality to quantify the health risks of the first winter cold spell in China on November 26th, 2022, and analyzed the reasons for the stronger development of the cold spell in terms of the circulation field.

Results

This cold spell was a result of the continuous reinforcement of the blocking high-pressure system in the Ural Mountains, leading to the deepening of the cold vortex in front of it. Temperature changes associated with the movement of cold fronts produced additional mortality risks and mortality burdens. In general, the average excess risk (ER) of death during the cold spell in China was 2.75%, with a total cumulative excess of 369,056 deaths. The health risks associated with temperatures were unevenly distributed spatially in China, with the ER values ranging from a minimum of 0.14% to a maximum of 5.72%, and temperature drops disproportionately affect southern regions of China more than northern regions. The cumulative excess deaths exibited the highest in eastern and central China, with 87,655 and 80,230 respectively, and the lowest in northwest China with 27,474 deaths. Among the provinces, excess deaths pronounced the highest in Shandong with 29,492 and the lowest in Tibet with only 196.

Conclusion

The study can provide some insight into the mortality burden of cold spells in China, while emphasising the importance of understanding the complex relationship between extreme low temperature events and human health. The outcomes could provide valuable revelations for informing pertinent public health policies.
Effects of dietary Astragalus membranaceus and Codonopsis pilosula extracts on growth performance, antioxidant capacity, immune status, and intestinal health in broilers
Authors: Liu Shun , Xiao Gengsheng , Wang Qi , Tian Jinpeng , Feng Xin , Zhang Qingyang , Gong Li
Published: December 2023

The objective of this study was to examine the effects of dietary Chinese herbal medicine (CHM) consisting of Astragalus membranaceus (Fisch.) Bunge (AMT) and Codonopsis pilosula (Franch.) Nannf (CPO) extracts on growth performance, antioxidant capacity, immune status, and intestinal health of broiler chickens. Two groups were formed, each consisting of six replicates of 12 one-day-old healthy male 817 white feather broilers. Broilers were fed either a basal diet (CON group) or a basal diet supplemented with 500 mg/kg CHM. The trial lasted 50 days. The results showed that CHM supplementation resulted in enhanced feed efficiency and antioxidant capacity in both the serum and liver, while it reduced uric acid and endotoxin levels, as well as diamine oxidase activity (p < 0.05). Additionally, CHM treatment increased the height of jejunum villi and upregulated Claudin-1 expression in the jejunal mucosa accompanied by an increase in the mRNA levels of interleukin-6 (IL-6), interferon-γ (IFN-γ), interferon-β (IFN-β), tumor necrosis factor-α (TNF-α), and anti-inflammatory cytokine interleukin-10 (IL-10) (p < 0.05). The presence of dietary CHM caused an increase in the proportions of Bacteroidetes and unclassified Bacteroidales but led to a decrease in those of Firmicutes and Alistipes (p < 0.05). The composition of the jejunal mucosa microbiota was correlated with the feed conversion ratio, serum metabolites, and gene expression based on Spearman correlation analysis. The findings indicated that the consumption of dietary CHM improved the utilization of feed, increased the mRNA expression of pro-inflammatory cytokines in the jejunal mucosa, and decreased the endotoxin level and activities of diamine oxidase and lactate dehydrogenase in the serum, which could potentially be linked to changes in the gut microbiota of broiler chickens.
A Study on Eddy Current Reduction Shape of Single-Phase Claw-Pole Motor
Authors: Jo Na-Rim , Lee Ye-Seo , Pyo Hyun-Jo , Jung Dong-Hoon , Kim Kwang-Soo , Kim Won-Ho
Published: December 2023

The claw-pole motor, known for its simple structure, is widely used in various fields due to its cost competitiveness. However, a drawback of the fixed-stator-type claw-pole motor is its vulnerability to eddy current losses. Therefore, this paper presents a single-phase claw-pole motor applied as a motor for cooling fans, with the aim of reducing eddy current losses and improving performance based on shape optimization, ultimately resulting in a single-phase claw-pole motor that meets the desired performance. The validity of this approach is verified through 3D finite element analysis (FEA).
Parameter Identification of Permanent Magnet Synchronous Motor with Dynamic Forgetting Factor Based on H∞ Filtering Algorithm
Authors: Yuan Tianqing , Chang Jiu , Zhang Yupeng
Published: December 2023

To address system parameter changes during permanent magnet synchronous motor (PMSM) operation, an H∞ filtering algorithm with a dynamic forgetting factor is proposed for online identification of motor resistance and inductance. First, a standard linear discrete PMSM parameter identification model is established; then, the discrete H∞ filtering algorithm is derived using game theory reducing state and measurement noise influence. A cost function is defined, solving extremes values of different terms. A dynamic forgetting factor is introduced to the weighted combination of initial and current measurement noise covariance matrices, eliminating identification issues from different initial values. On this basis, a dynamic forgetting factor is added to weigh the combination of the initial measurement noise covariance matrix and the current measurement noise covariance matrix, which eliminates the influence of the discrimination error caused by the different initial values. Finally, the identification model is built in MATLAB/Simulink for simulation analysis to verify the feasibility of the proposed algorithm. The simulation results show the proposed H∞ filtering algorithm rapidly and accurately identifies resistance and inductance values with significantly improved robustness. The forgetting factor enables quick stable recognition even with poor initial values, enhancing PMSM control performance.
An Accurate Dynamic Model Identification Method of an Industrial Robot Based on Double-Encoder Compensation
Authors: Liu Xun , Xu Yan , Song Xiaogang , Wu Tuochang , Zhang Lin , Zhao Yanzheng
Published: December 2023

Aiming at the challenges to accurately simulate complex friction models, link dynamics, and part uncertainty for high-precision robot-based manufacturing considering mechanical deformation and resonance, this study proposes a high-precision dynamic identification method with a double encoder. Considering the influence of the dynamic model of the manipulator on its control accuracy, a three-iterative global parameter identification method based on the least square method and GMM (Gaussian Mixture Model) under the optimized excitation trajectory is proposed. Firstly, a bidirectional friction model is constructed to avoid using residual torque to reduce the identification accuracy. Secondly, the condition number of the block regression matrix is used as the optimization objective. Finally, the joint torque is theoretically identified with the weighted least squares method. A nonlinear model distinguishing between high and low speeds was established to fit the nonlinear friction of the robot. By converting the position and velocity of the motor-side encoder to the linkage side using the deceleration ratio, the deformation quantity could be calculated based on the discrepancy between theoretical and actual values. The GMM algorithm is used to compensate the uncertainty torque that was caused by model inaccuracy. The effectiveness of the proposed method is verified by a simulation and experiment on a 6-DoF industrial robot. Results prove that the proposed method can enhance the online torque estimation performance by up to 20%.
Development of Ethyl Formate Disinfestation Treatment Methods for the Prevention of the Introduction and Establishment of Exotic Insect Pests in Greenhouse Cultivation
Authors: Kim Kyeongnam , Kim Dongbin , Kim Chaeeun , Kim Donghyeon , Kim Byeongjun , Lee Byung-Ho , Lee Sung-Eun
Published: December 2023

Globalization has increased international trade and caused an annual increase in the number of non-native insect pest species found in quarantine sites in Korea. Since over 80% of Korean farms use greenhouses with internal conditions conducive to growing crops and hospitable to exotic pests, efficient pest control is crucial. This study evaluated the efficacy of ethyl formate (EF) against three major exotic insect pests (Aphis gossypii, Frankliniella occidentalis, and Tetranychus urticae) and beneficial organisms (earthworms, honeybees, and silkworms) via EF fumigation experiments at two concentrations. The lethal concentration–time (LCt)99 values of A. gossypii, F. occidentalis, and T. urticae were 8.96, 14.00, and 19.07 g h/m3, respectively. Four hours of fumigation of EF at 15 g/m3 left no residue on the crops or soil after a maximum of 3 h. The beneficial organisms exhibited higher tolerance levels than A. gossypii with regard to LCt99 value, but the higher EF treatment dosage needed to control F. occidentalis and T. urticae could be highly lethal to honeybees. The lower EF dose (4 g/m3) effectively controlled A. gossypii, but 15 g/m3 was needed for F. occidentalis and T. urticae. Phytotoxicity varied in severity with EF concentration. These insights can help in developing a refined disinfestation strategy for greenhouses.
Metagenomics of the Effect of Long-Term Straw Return on the Phosphorus Cycle in Meadow Black Soil
Authors: Wang Chengyu , Wang Dong , Li Yanan , Liu Shuxia
Published: December 2023

Returning crop straw to the soil is an effective measure to increase soil fertility and maintain crop yield in agroecosystems. In this study, we conducted a 34-year field experiment (1984–2017) to investigate the relationships among the impacts of straw return on soil nutrients, phosphorus (P) fractions, phosphorus transformation-related functional microbial communities, and key genes in black soil. The results of the soil chemical properties showed that straw return could slow the decline in soil pH and increase soil nutrients, i.e., soil organic carbon (SOC), available K (AK), and available P (AP) concentrations, with the straw addition (PKS) treatment resulting in the highest soil AP and AK contents. Compared with conventional fertilizer (NPK) and conventional fertilizer with straw (NPKS), straw return alone (S) significantly increased the soil AP and AK contents by 1.1–42.8 and 38.3–114.3 mg/kg (p < 0.05), respectively. The results of the phosphorus fraction experiment indicated that long-term straw return promoted labile and moderately stable phosphorus content by altering the composition and increasing the relative abundances of functional genes regulating soil P activation (ugpQ, ppk, phoD, and gcd). The compositional changes in the phosphorus-cycling-related functional genes of the soil were affected mostly by soil total P (TP), AK, and NO3−-N, whereas pH, SOC, and available N (AN) were the main environmental factors influencing the phosphorus-cycling-related microbial community composition. These direct measurements provide insight into the soil phosphorus fractions, phosphorus-cycling-related functional genes, and microbial communities associated with straw returning, which enhances our understanding of the chemical and biogeochemical behavior of soil phosphorus upon straw incorporation.
Three-Dimensional Velocity Field Interpolation Based on Attention Mechanism
Authors: Yao Xingmiao , Cui Mengling , Wang Lian , Li Yangsiwei , Zhou Cheng , Su Mingjun , Hu Guangmin
Published: December 2023

The establishment of a three-dimensional velocity field is an essential step in seismic exploration, playing a crucial role in understanding complex underground geological structures. Accurate 3D velocity fields are significant for seismic imaging, observation system design, precise positioning of underground geological targets, structural interpretation, and reservoir prediction. Therefore, obtaining an accurate 3D velocity field is a focus and challenge in this field of study. To achieve intelligent interpolation of the 3D velocity field more accurately, we have built a network model based on the attention mechanism, JointA 3DUnet. Based on the traditional U-Net, we have added triple attention blocks and channel attention blocks to enhance dimension information interaction, while adapting to the different changes of geoscience data in horizontal and vertical directions. Moreover, the network also incorporates dilated convolution to enlarge the receptive field. During the training process, we introduced transfer learning to further enhance the network’s performance for interpolation tasks. At the same time, our method is a deep learning interpolation algorithm based on an unsupervised model. It does not require a training set and learns information solely from the input data, automatically interpolating the missing velocity data at the missing positions. We tested our method on both synthetic and real data. The results show that, compared with traditional intelligent interpolation methods, our approach can effectively interpolate the three-dimensional velocity field. The SNR increased to 36.22 dB, and the pointwise relative error decreased to 0.89%.
Defects Detection on 110 MW AC Wind Farm’s Turbine Generator Blades Using Drone-Based Laser and RGB Images with Res-CNN3 Detector
Authors: Masita Katleho , Hasan Ali , Shongwe Thokozani
Published: December 2023

An effective way to perform maintenance on the wind turbine generator (WTG) blades installed in grid-connected wind farms is to inspect them using Unmanned Aerial Vehicles (UAV). The ability to detect wind turbine blade defects from these laser and RGB images captured by drones has been the subject of numerous studies. The issue that most applied techniques battle with is being able to locate different wind turbine blade defects with high confidence scores and precision. The accuracy of these models’ defect detection decreases due to varying testing image scales. This article proposes the Res-CNN3 technique for detecting wind turbine blade defects. In Res-CNN3, defect region detection is achieved through a bipartite process that processes the laser delta and RGB delta structure of a wind turbine blade image with an integration of residual networks and concatenated CNNs to determine the presence of typical defect regions in the image. The loss function is logistic regression, and a Selective Search (SS) algorithm is used to predict the regions of interest (RoI) of the input images for defects detection. Several experiments are conducted, and the outcomes prove that the proposed model has a high prospect for accuracy in solving the problem of defect detection in a manner similar to the advanced benchmark methods.
Biomechanical Analysis of the Impact of Transverse Connectors of Pedicle-Screw-Based Fixation on Thoracolumbar Compression Fracture
Authors: Szkoda-Poliszuk Klaudia , Żak Małgorzata , Załuski Rafał , Pezowicz Celina
Published: December 2023

Contemporary clinical practice is progressively shifting towards percutaneous minimally invasive surgery. Conversely, the incorporation of transverse connectors in the design of spinal fixation systems is associated with more invasive open surgical procedures. The primary objective of this investigation was to evaluate the influence of transverse connectors in posterior spinal fixation system designs in cases involving vertebral compression fractures, specifically on selected mechanical parameters of the thoracolumbar spine in situations of instability. This research objective was achieved through a combination of experimental tests and numerical simulations. From the experimental tests conducted, critical mechanical parameters were ascertained, including the bending stiffness coefficient and energy dissipation. Numerical simulations were employed to determine additional parameters, such as the angular range of motion for individual spinal segments, intradiscal pressure within individual intervertebral discs, and stress distribution on the articular facets. Analyzing the impact of transverse connectors on the obtained results revealed that their inclusion in a fixation system results in a minor increase in stiffness and a decrease in mobility in comparison to fixation systems devoid of connectors. These findings create the potential for utilizing minimally invasive surgery as a viable alternative to open surgical procedures.
Deep-Learning-Based Approach for Automated Detection of Irregular Walking Surfaces for Walkability Assessment with Wearable Sensor
Authors: Ng Hui R. , Zhong Xin , Nam Yunwoo , Youn Jong-Hoon
Published: December 2023

A neighborhood’s walkability is associated with public health, economic and environmental benefits. The state of the walking surface on sidewalks is a key factor in assessing walkability, as it promotes pedestrian movement and exercise. Yet, conventional practices for assessing sidewalks are labor-intensive and rely on subject-matter experts, rendering them subjective, inefficient and ineffective. Wearable sensors can be utilized to address these limitations. This study proposes a novel classification method that employs a long short-term memory (LSTM) network to analyze gait data gathered from a single wearable accelerometer to automatically identify irregular walking surfaces. Three different input modalities—raw acceleration data, single-stride and multi-stride hand-crafted accelerometer-based gait features—were explored and their effects on the classification performance of the proposed method were compared and analyzed. To verify the effectiveness of the proposed approach, we compared the performance of the LSTM models to the traditional baseline support vector machine (SVM) machine learning method presented in our previous study. The results from the experiment demonstrated the effectiveness of the proposed framework, thereby validating its feasibility. Both LSTM networks trained with single-stride and multi-stride gait feature modalities outperformed the baseline SVM model. The LSTM network trained with multi-stride gait features achieved the highest average AUC of 83%. The classification performance of the LSTM model trained with single-stride gait features further improved to an AUC of 88% with post-processing, making it the most effective model. The proposed classification framework serves as an unbiased, user-oriented tool for conducting sidewalk surface condition assessments.
Building Cyber-Resilient Smart Grids with Digital Twins and Data Spaces
Authors: Coppolino Luigi , Nardone Roberto , Petruolo Alfredo , Romano Luigi
Published: December 2023

The rapid expansion of digital twin technology has revolutionized management and testing across various sectors, particularly in safeguarding critical infrastructure like smart grids. Aligned with the NIS2 Directive, Directive (EU) 2022/2555 of the European Parliament and of the Council of 14 December 2022, digital twins play a critical role in bolstering cybersecurity measures by enabling advanced simulation and real-time monitoring, key aspects emphasized in the directive for enhancing the security of networks and information systems. Concurrently, Europe’s shift towards communal data spaces amplifies the need for robust cyber defences. This paper aims to bolster cybersecurity defences in critical infrastructure, with a particular focus on the energy sector and smart grids. It proposes an innovative architecture for cybersecurity monitoring, converting a Common Information Model-compliant system into a digital twin via the FIWARE platform and incorporating an open-source Security Information and Event Management solution. Validated by a real-world case study, our approach demonstrates significant advancements in protecting smart grids against cyber threats.
Identification of Surface Deformation-Sensitive Features under Extreme Rainfall Conditions in Zhengzhou City Based on Multi-Source Remote Sensing Data
Authors: Han Long , Cao Lianhai , Wu Qifan , Huang Jia , Yu Baobao
Published: December 2023

Extreme precipitation is one of the most prevalent meteorological disasters occurring today. Its occurrence not only causes significant social and economic losses but also indirectly affects surface deformation, creating safety hazards for diverse ground features. Although there are presently high-precision, comprehensive tools such as continuous scattering interferometry to observe surface deformation, it takes a long time to locate potentially vulnerable objects. A monitoring scheme for surface deformation anomalies was devised to address the timeliness issue of identifying sensitive surface features under extreme rainfall conditions. An SAR image of Sentinel-1A is used to derive the surface deformation in three years before and after a rainstorm in the main urban area of Zhengzhou, and the anomaly surface deformation objects after extreme precipitation are screened to determine the surface deformation-sensitive objects. The results indicate that, in the past three years, a 22.14 km2 area in Zhengzhou City has experienced a settlement speed greater than 10 mm/yr. Under the influence of the “7–20” rainstorm in the main urban area of Zhengzhou City, among them, the area of highly sensitive agricultural land for deformation is 2,581,215 m2, and there are 955 highly sensitive houses for deformation, with an excellent recognition effect. This method is effective in rapidly locating surface deformation-sensitive or potentially damaged features; it can provide a reference for the vulnerability and risk assessment of buildings.