bluuebunny/crossref_metadata_2025 huggingface dataset:
Detrimental Effects of Anti-Nucleocapsid Antibodies in SARS-CoV-2 Infection, Reinfection, and the Post-Acute Sequelae of COVID-19
Authors: Nakayama Emi E. , Shioda Tatsuo
Published: December 2024

Antibody-dependent enhancement (ADE) is a phenomenon in which antibodies enhance subsequent viral infections rather than preventing them. Sub-optimal levels of neutralizing antibodies in individuals infected with dengue virus are known to be associated with severe disease upon reinfection with a different dengue virus serotype. For Severe Acute Respiratory Syndrome Coronavirus type-2 infection, three types of ADE have been proposed: (1) Fc receptor-dependent ADE of infection in cells expressing Fc receptors, such as macrophages by anti-spike antibodies, (2) Fc receptor-independent ADE of infection in epithelial cells by anti-spike antibodies, and (3) Fc receptor-dependent ADE of cytokine production in cells expressing Fc receptors, such as macrophages by anti-nucleocapsid antibodies. This review focuses on the Fc receptor-dependent ADE of cytokine production induced by anti-nucleocapsid antibodies, examining its potential role in severe COVID-19 during reinfection and its contribution to the post-acute sequelae of COVID-19, i.e., prolonged symptoms lasting at least three months after the acute phase of the disease. We also discuss the protective effects of recently identified anti-spike antibodies that neutralize Omicron variants.
BLV-CoCoMo Dual qPCR Assay Targeting LTR Region for Quantifying Bovine Leukemia Virus: Comparison with Multiplex Real-Time qPCR Assay Targeting pol Region
Authors: Watanuki Sonoko , Bao Aronggaowa , Saitou Etsuko , Shoji Kazuyuki , Izawa Masaki , Okami Mitsuaki , Matsumoto Yasunobu , Aida Yoko
Published: December 2024

The proviral load (PVL) of the bovine leukemia virus (BLV) is a useful index for estimating disease progression and transmission risk. Real-time quantitative PCR techniques are widely used for PVL quantification. We previously developed a dual-target detection method, the “Liquid Dual-CoCoMo assay”, that uses the coordination of common motif (CoCoMo) degenerate primers. This method can detect two genes simultaneously using a FAM-labeled minor groove binder (MGB) probe for the BLV long terminal repeat (LTR) region and a VIC-labeled MGB probe for the BoLA-DRA gene. In this study, we evaluated the diagnostic and analytical performance of the Dual-CoCoMo assay targeting the LTR region by comparing its performance against the commercially available Takara multiplex assay targeting the pol region. The diagnostic sensitivity and specificity of the Liquid Dual-CoCoMo assay based on the diagnostic results of the ELISA or original Single-CoCoMo qPCR were higher than those of the Takara multiplex assay. Furthermore, using a BLV molecular clone, the analytical sensitivity of our assay was higher than that of the Takara multiplex assay. Our results provide the first evidence that the diagnostic and analytical performances of the Liquid Dual-CoCoMo assay are better than those of commercially available multiplex assays that target the pol region.
Small Molecules in Parkinson’s Disease Therapy: From Dopamine Pathways to New Emerging Targets
Authors: Lee Hwayoung , Elkamhawy Ahmed , Rakhalskaya Polina , Lu Qili , Nada Hossam , Quan Guofeng , Lee Kyeong
Published: December 2024

Parkinson’s disease (PD) is a chronic, progressive neurological disorder affecting approximately 10 million people worldwide, with prevalence expected to rise as the global population ages. It is characterized by the degeneration of dopamine-producing neurons in the substantia nigra pars compacta, leading to motor symptoms such as tremor, rigidity, bradykinesia, postural instability, and gait disturbances, as well as non-motor symptoms including olfactory disturbances, sleep disorders, and depression. Currently, no cure exists for PD, and most available therapies focus on symptom alleviation. This dopamine deficiency impairs motor control, and since dopamine itself cannot cross the blood–brain barrier (BBB), the precursor L-Dopa is commonly used in treatment. L-Dopa is administered with enzyme inhibitors to prevent premature conversion outside the brain, allowing it to cross the BBB and convert to dopamine within the central nervous system. Although these therapies have improved symptom management, recent research has revealed additional molecular factors in PD pathology, such as α-synuclein aggregation, mitochondrial dysfunction, and lysosomal abnormalities, contributing to its complexity. These discoveries open up possibilities for neuroprotective therapies that could slow disease progression. In this review, we categorize PD therapeutic targets into two main groups: currently used therapies and targets under active research. We also introduce promising small-molecule compounds studied between 2019 and 2023, which may represent future treatment options. By examining both established and emerging targets, we aim to highlight effective strategies and potential directions for future drug development in Parkinson’s disease therapy.
Bufadienolides from Chansu Injection Synergistically Enhances the Antitumor Effect of Erlotinib by Inhibiting the KRAS Pathway in Pancreatic Cancer
Authors: Guo Yanli , Jin Yu , Gao Jie , Wang Ding , Wang Yanming , Shan Liya , Yang Mengyu , Li Xinzhi , Ma Ketao
Published: December 2024

Background and Objectives: The Chansu injection (CSI), a sterile aqueous solution derived from Chansu, is applied in clinical settings to support antitumor and anti-radiation treatments. CSI’s principal active components, bufadienolides (≥90%), demonstrate potential effects on pancreatic cancer (PDAC), but their underlying mechanisms remain unclear. This study aimed to elucidate the antitumor effects and pathways associated with CSI in PDAC. Methods: Network pharmacology and bioinformatics analyses explored CSI’s mechanisms against PDAC. MTT, colony-formation, and migration assays evaluated CSI’s impact on proliferation and migration in PANC-1 and MIA PACA-2 cells, both as a single agent and in combination with erlotinib (EGFR inhibitor). Cell cycle analysis employed flow cytometry. Animal experiments were performed on tumor-bearing mice, with targets and pathways assessed via molecular docking and western blotting. Results: CSI treatment suppressed PDAC cell proliferation and migration by inducing G2/M phase arrest. Network pharmacology, bioinformatics, and molecular docking indicated that CSI’s anti-PDAC effects may involve EGFR pathway modulation, with CSI lowering p-EGFR/KRAS/p-ERK1/2 pathway expressions in PDAC cells. Additionally, sustained KRAS activation in mediating erlotinib resistance in PDAC and CSI potentiated erlotinib’s antitumor effects through enhanced KRAS and p-ERK1/2 inhibition. CSI also enhanced erlotinib’s efficacy in tumor-bearing mice without causing detectable toxicity in renal, cardiac, or hepatic tissues at therapeutic doses. Conclusions: CSI as an adjuvant used in antitumor and anti-radiation therapies enhanced erlotinib’s antitumor effects through modulation of the KRAS pathway. CSI and erlotinib’s synergistic interaction represents a promising approach for addressing erlotinib resistance in PDAC treatment.
Experimental and Theoretical Design on the Development of Matrix Tablets with Multiple Drug Loadings Aimed at Optimizing Antidiabetic Medication
Authors: Sha’at Mousa , Ochiuz Lacramioara , Rusu Cristina Marcela , Agop Maricel , Barsan (Bujor) Alexandra , Cretan Monica Stamate , Hartan Mihaela , Spac Adrian Florin
Published: December 2024

Background: Diabetes is a growing global health crisis that requires effective therapeutic strategies to optimize treatment outcomes. This study aims to address this challenge by developing and characterizing extended-release polymeric matrix tablets containing metformin hydrochloride (M-HCl), a first-line treatment for type 2 diabetes, and honokiol (HNK), a bioactive compound with potential therapeutic benefits. The objective is to enhance glycemic control and overall therapeutic outcomes through an innovative dual-drug delivery system. Methods: The tablets were formulated using hydrophilic polymers, such as Carbopol® 71G NF and Noveon® AA-1. The release kinetics of M-HCl and HNK were investigated through advanced mathematical models, including fractal and multifractal dynamics, to capture the non-linear and time-dependent release processes. Traditional kinetic models (zero-order, first-order, Higuchi equations) were also evaluated for comparison. In vitro dissolution studies were conducted to determine the release profiles of the active ingredients under varying polymer concentrations. Results: The study revealed distinct release profiles for the two active ingredients. M-HCl exhibited a rapid release phase, with 80% of the drug released within 4–7 h depending on polymer concentration. In contrast, HNK demonstrated a slower release profile, achieving 80% release after 9–10 h, indicating a greater sensitivity to polymer concentration. At shorter intervals, drug release followed classical kinetic models, while multifractal dynamics dominated at longer intervals. Higher polymer concentrations resulted in slower drug release rates due to the formation of a gel-like structure upon hydration, which hindered drug diffusion. The mechanical properties and stability of the matrix tablets confirmed their suitability for extended-release applications. Mathematical modeling validated the experimental findings and provided insights into the structural and time-dependent factors influencing drug release. Conclusions: This study successfully developed dual-drug extended-release matrix tablets containing metformin hydrochloride and honokiol, highlighting the potential of hydrophilic polymers to regulate drug release. The findings emphasize the utility of advanced mathematical models for predicting release kinetics and underscore the potential of these formulations to improve patient compliance and therapeutic outcomes in diabetes management.
Coherence Properties of a Supercontinuum Generated by Cascade Raman Processes in a Hollow-Core Fiber Filled with a Mixture of Deuterium and Hydrogen
Authors: Yatsenko Yury , Pryamikov Andrey , Gladyshev Alexey
Published: December 2024

Here, we report a numerical study of supercontinuum generation in an antiresonant optical fiber with a hollow core filled with a mixture of deuterium (D2) and hydrogen (H2). For 1 ps pulses at a wavelength of 1.03 μm with different chirp values, we demonstrate a possibility of obtaining a mid-IR coherent supercontinuum with a spectral width of 2300 nm, initiated by cascade processes at resonance frequencies of vibrational and rotational levels of D2 and H2. We show that an increase in the chirped pulse duration to 25 ps while maintaining the energy and spectral width allows increasing the quantum conversion efficiency in the mid-IR from 10 to 50% and expanding the range of optimal fiber lengths at which a high degree of supercontinuum coherence is achieved.
Broadband Thermo-Optic Photonic Switch for TE and TM Modes with Adiabatic Design
Authors: Hashemi Babak , Casalino Maurizio , Crisci Teresa , Mammeri Mohamed , Della Corte Francesco G.
Published: December 2024

Optical power switches are essential components in fiber optic communication systems, requiring minimal losses, a broad operating wavelength range, and high tolerance to fabrication errors for optimal performance. Adiabatic optical power switches inherently meet these criteria and are well suited for manufacturing processes which support large-scale production at low costs. This paper presents the design and simulation of an adiabatic switch with a flat response in the whole 1525–1625 nm wavelength range (C band and L band) for both TE and TM polarizations. The switch is based on the thermo-optic effect induced by local variations in temperature. The impacts of the design parameters, such as the device length and dissipated heat, are analyzed. The simulation results indicate that the switch achieved high efficiency and low insertion losses, highlighting the potential of adiabatic switches for reliable and scalable integration into advanced optical circuits.
Cycloplegia Improves the Inter-Optometrist Repeatability of Subjective Refraction
Authors: Carpena-Torres Carlos , Rodríguez-Lafora Maria , Pastrana Cristina , Privado-Aroco Ana , Serramito María , Batres Laura , Carracedo Gonzalo
Published: December 2024

Background: Since accommodation may be a source of error affecting the inter-optometrist repeatability of subjective refraction, this study investigated whether the use of cycloplegia could improve this repeatability. Methods: A randomized cross-sectional study was conducted on 42 young hyperopes (18.2 ± 7.7 years, range 6 to 31 years). Subjective refraction was performed by two different optometrists in two measurement sessions: one day without cycloplegia and, on a different day, with cycloplegia, in random order. The inter-optometrist repeatability of all refractive variables (M, J0, and J45) was analyzed, selecting one eye randomly, in terms of the 95% confidence interval of repeatability (r). Results: No statistically significant differences were found between the optometrists for any refractive variable, both with and without cycloplegia (p ≥ 0.05). Furthermore, no correlation was found between participants’ age and the refractive differences between optometrists under both cycloplegic conditions (p ≥ 0.05). However, the use of cycloplegia improved the inter-optometrist repeatability of M (r = 0.37 D) compared to the non-cycloplegic measurements (r = 0.62 D). Conclusions: These results suggest that accommodation in young hyperopes is likely a primary source of error that could explain the discrepancies in subjective refraction between optometrists.
Mayan Medicinal Plants Bignonia potosina and Thouinia paucidentata Demonstrate Anti-Infective Properties Against the Priority Antibiotic-Resistant Bacteria Acinetobacter baumannii and Pseudomonas aeruginosa
Authors: Molina-Salinas Gloria María , Dzul-Beh Angel , Uc-Cachón Andrés Humberto , Dzib-Baak Haziel Eleazar , González-Sánchez Avel Adolfo , Palma-Pech Geovani Antonio , Quintal-Novelo Carlos Javier
Published: December 2024

(1) Background: Carbapenem-resistant Acinetobacter baumannii (CBRAB) and Pseudomonas aeruginosa (CBRPA) are critical and high-priority pathogens that require new therapeutic developments. Medicinal plants are valuable pharmaceutical resources. This study explored the anti-infective properties of Mayan plants, Bignonia potosina, and Thouinia paucidentata. (2) Methods: Plant parts were extracted using n-hexane, and their ability to inhibit bacterial growth and counteract resistance mechanisms and virulence factors in CBRAB and CBRPA was assessed. GC-MS analysis of the composition of the non-polar extracts and chemometric techniques correlated the phytoconstituents with anti-infective properties. (3) Results: Bignonia potosina liana and flower extracts exhibited potent antibacterial activity against A. baumannii strains (MIC 15.7 to 250 µg/mL) and moderate activity against P. aeruginosa strains (MIC 250 to 1000 µg/mL). Thouinia paucidentata leaf extract at 1000 µg/mL reduced imipenem MIC by 2048-fold for CBRAB, and B. potosina flower extract significantly inhibited A. baumannii catalase activity (at 62.5 µg/mL) and reduced P. aeruginosa pyocyanin production (at 1000 µg/mL). Chemometric analysis identified fatty acids, fatty acid amides, terpenes, and higher alkanes as contributors to their anti-infective properties. (4) Conclusions: This study highlights the potential of medicinal plants in the development of novel anti-infective therapies against CBRAB and CBRPA with various targets.
Combined Physiological and Transcriptomic Analyses of the Effects of Exogenous Trehalose on Salt Tolerance in Maize (Zea mays L.)
Authors: He Jingyi , Tang Hongliang
Published: December 2024

Soil salinization severely affects the quality and yield of maize. As a C4 plant with high efficiency in utilizing light and carbon dioxide, maize (Zea mays L.) is one of the most important crops worldwide. This study aims to investigate the pathways and mechanisms by which trehalose mediates the improvement of salt tolerance in maize through a combined analysis of physiology and transcriptomics. The results indicate that foliar application of trehalose treatment significantly increased maize biomass and antioxidant enzyme activity while reducing the H2O2 and Na+/K+ ratios in both the aerial and underground parts of the plant. Additionally, trehalose enhanced the total secretion of organic acids from maize roots, improving the soil microenvironment for maize growth under salt stress and alleviating Na+ toxicity. Transcriptomic data revealed that under salt stress, most differentially expressed genes (DEGs) were enriched in pathways related to photosynthesis, abscisic acid signaling, and sugar metabolism, and trehalose application increased the expression levels of these pathways, thereby mitigating the growth inhibition caused by salinity. This study elucidates mechanisms for enhancing salt tolerance in maize, providing theoretical support for improving its resilience and offering innovative strategies for utilizing a wide range of saline-alkali land.
Simultaneous Down-Regulation of Dominant Cinnamoyl CoA Reductase and Cinnamyl Alcohol Dehydrogenase Dramatically Altered Lignin Content in Mulberry
Authors: Huang Shuai , Kang Xiaoru , Fu Rumeng , Zheng Longyan , Li Peijun , Tang Fengjuan , Chao Nan , Liu Li
Published: December 2024

Mulberry (Morus alba L.) is a significant economic tree species in China. The lignin component serves as a critical limiting factor that impacts both the forage quality and the conversion efficiency of mulberry biomass into biofuel. Cinnamoyl CoA reductase (CCR; EC 1.21.1.44) and cinnamyl alcohol dehydrogenase (CAD; EC 1.1.1.95) are the key enzymes that catalyze the final two reductive steps in the biosynthesis of monolignols. In this study, we conducted a comprehensive functional analysis to validate the predominant CCR genes involved in monolignol biosynthesis. In this study, we initially validated the predominant CCR genes implicated in monolignol biosynthesis through an extensive functional analysis. Phylogenetic analysis, tissue-specific expression profiling and enzymatic assays indicated that MaCCR1 is the authentic CCR involved in lignin biosynthesis. Furthermore, the expression level of MaCCR1 exhibited a significant positive correlation with lignin content, and the down-regulation of MaCCR1 via virus-induced gene silencing resulted in altered lignin content in mulberry. The down-regulation of MaCCR1 and MaCAD3/4, both individually and concurrently, exhibited markedly different effects on lignin content and mulberry growth. Specifically, the simultaneous down-regulation of MaCCR1 and MaCAD3/4 significantly altered lignin content in mulberry, resulting in dwarfism of the plants. Conversely, the down-regulation of MaCAD3/4 alone not only decreased lignin content but also led to an increase in biomass. These findings offer compelling evidence elucidating the roles of MaCCRs in mulberry and identify specific target genes, thereby providing a crucial foundation for the genetic modification of lignin biosynthesis.
Development of Roselle (Hibiscus sabdariffa L.) Transcriptome-Based Simple Sequence Repeat Markers and Their Application in Roselle
Authors: Tao Aifen , Li Yunqing , Chen Jihan , Li Jing , Xu Jiantang , Lin Lihui , Zhang Liwu , Fang Pingping
Published: December 2024

Roselle (Hibiscus sabdariffa L.) simple sequence repeat (SSR) markers were developed using RNA sequencing technology, providing a foundation for genetic analysis and the identification of roselle varieties. In this study, 10 785 unigenes containing 12 994 SSR loci with an average of one SSR locus per 6.87 Kb were identified, and the occurrence frequency of the SSR loci was 11.36%. Trinucleotide repeat motifs were the most abundant, followed by dinucleotide repeats, with AAG/CTT and AT/AT being the predominant types, respectively. After screening 100 primer pairs with a polymorphic ratio of 32.0%, we obtained 32 primer pairs, resulting in clear and stable polymorphic bands. Twenty-seven primer pairs were highly or moderately polymorphic, and seven primer pairs were highly polymorphic. Genetic relationship analysis based on the selected SSR primers showed that 38 roselle accessions were classified into different clades, with those from the same regions clustered into the same subgroups. In contrast, individuals with unique morphological traits were separated. DNA fingerprints of 38 roselle varieties were constructed using five SSR primers, providing an effective method for identifying roselle varieties at a molecular level. Our data provide novel insights into the genetics of H. sabdariffa and may be used in SSR-assisted roselle breeding.
Accounting for the Structure–Property Relationship of Hollow-Fiber Membranes in Modeling Hemodialyzer Clearance
Authors: Kozmai Anton , Porozhnyy Mikhail , Gil Violetta , Butylskii Dmitrii , Lopatin Dmitry , Rodichenko Aleksey , Voroshilov Igor , Mareev Artem , Nikonenko Victor
Published: December 2024

The relevance of the hemodialysis procedure is increasing worldwide due to the growing number of patients suffering from chronic kidney disease. Taking into account the structure of dialysis polymer membranes is an important aspect in their development to achieve the required performance of hemodialyzers. We propose a new mathematical model of mass transfer that allows hollow-fiber membrane structural parameters to be taken into account in simulating the clearance (CL) of hemodialyzers in a way that does not require difficult to achieve close approximation to the exact geometry of the membrane porous structure. The model was verified by a comparison of calculations with experimental data on CL obtained using a lab-made dialyzer as well as commercially available ones. The simulations by the model show the non-trivial behavior of the dialyzer clearance as a function of membrane porosity (fp) and the arrangement of pores (α). The analysis of this behavior allows one to consider two strategies for increasing the CL of the dialyzer by optimizing the polymer membrane structure: (1) creating a membrane with a well-structured pore system (where α → 1) since doubling α at a high enough fp can lead to an almost tenfold increase in CL; (2) increasing the porosity of the membrane characterized by a random arrangement of pores (α → 0), where, at a relatively low α, a sharp increase in CL is observed with a small increase in fp over a certain threshold value.
Overcoming Challenges in the Commercialization of Biopolymers: From Research to Applications—A Review
Authors: Schick Simon , Heindel Julia , Groten Robert , Seide Gunnar H.
Published: December 2024

Biopolymers are promising sustainable alternatives to petrochemical polymers, but the recent increase in published research articles has not translated into marketable products. Here, we discuss barriers to market entry by exploring application-specific, ecological, and economic aspects, such as the utilization of biodegradable polymers to mitigate the accumulation of microplastics. We summarize previous studies revealing how fiber surface properties and the dwell time during fiber spinning affect degradability. We show how biopolymers can be processed on existing machines and how degradability can be tailored by changing process parameters. This novel approach, known as degradation by design, will allow us to rethink product development and ensure that biopolymers are not only able to replace petrochemical polymers but also reduce the environmental harm they cause.
Green Recycling for Polypropylene Components by Material Extrusion
Authors: Spina Roberto , Gurrado Nicola
Published: December 2024

High volumetric shrinkage and rheological behavior of polypropylene (PP) are the main problems that make material extrusion (MEX) uncommon for this material. The complexity is raised when recycled materials are used. This research covered different aspects of the MEX process of virgin and recycled PP, from the analysis of rough materials to the mechanical evaluation of the final products. Two types of virgin PP (one in pellet and the other in filament form) and one recycled PP were analyzed. Thermal characterization and rheological analysis of these materials were initially employed to understand the peculiar properties of all investigated PP and set filament extrusion. The 3D parts were then printed using processed filaments to check fabrication quality through visual analysis and mechanical tests. A well-structured approach was proposed to encompass the limitations of PP 3D printing by accurately evaluating the influence of the material properties on the final part performance. The results revealed that the dimensional and mechanical performances of the recycled PP were comparable with the virgin filament commonly employed in MEX, making it particularly suitable for this application.
Investigation of a Cogeneration System Combining a Solid Oxide Fuel Cell and the Organic Rankine Cycle: Parametric Analysis and Multi-Objective Optimization
Authors: Yang Sheng , Liang Anman , Jin Zhengpeng , Xie Nan
Published: December 2024

A novel solid oxide fuel cell (SOFC)-based cogeneration system is proposed here, integrating an organic Rankine cycle for waste heat recovery. Technical–economic and parametric analyses are conducted, and a multi-objective optimization is carried out. The results reveal that the net electrical efficiency, investment cost, and payback time are 56.6%, USD 2,408,256, and 3.27 years, respectively. The parametric analysis indicates that the current density should be limited between 0.3 A/cm2 and 0.9 A/cm2, and the stack temperature should be controlled between 675 °C and 875 °C. After the operational optimization of ηele-CostTCI, the investment cost and the net electrical efficiency are obtained as USD 2,164,742 and 62.1%. After the ηele-PBT optimization, the payback period and the net electrical efficiency are 3.22 years and 58.9%. The heat transfer network optimization achieves the highest efficiency and reduces the cold utilities by 43 kW, but three additional heat exchangers should be added to the system. This research provides practical reference and pragmatic guidance for the integration, analysis, operation, and heat transfer network optimization of SOFC-based cogeneration systems.
Resilient, Adaptive Industrial Self-X AI Pipeline with External AI Services: A Case Study on Electric Steelmaking
Authors: Kannisto Petri , Kargar Zeinab , Alvarez Gorka , Kleimt Bernd , Arteaga Asier
Published: December 2024

The introduction of Self-X capabilities into industrial control offers a tremendous potential in the development of resilient, adaptive production systems that enable circular economy. The Self-X capabilities, powered by Artificial Intelligence (AI), can monitor the production performance and enable timely reactions to problems or suboptimal operation. This paper presents a concept and prototype for Self-X AI in the process industry, particularly electric steelmaking with the EAF (Electric Arc Furnace). Due to complexity, EAF operation should be optimized with computational models, but these suffer from the fluctuating composition of the input materials, i.e., steel scrap. The fluctuation can be encountered with the Self-X method that monitors the performance, detecting anomalies and suggesting the re-training and re-initialization of models. These suggestions support the Human-in-the-Loop (HITL) in managing the AI models and in operating the production processes. The included Self-X capabilities are self-detection, self-evaluation, and self-repair. The prototype proves the concept, showing how the optimizing AI pipeline receives alarms from the external AI services if the performance degrades. The results of this work are encouraging and can be generalized, especially to processes that encounter drift related to the conditions, such as input materials for circular economy.
Gas Charging Characteristics and Controlling Factors in Tight Sandstone Reservoir of Xujiahe Formation, Sichuan Basin
Authors: Xie Zengye , Rui Yurun , Guo Jianying , Li Jian , Yang Rongjun , Guo Du , Han Shuangbiao
Published: December 2024

The tight reservoirs in the Sichuan Basin generally contain water and have complex gas–water relationships. The dynamic changes and main controlling factors of natural gas injection are unclear, which has had a serious impact on the exploration and development of tight sandstone gas. This article selects samples from Yongqian and Qiulin gas fields to characterize the reservoir characteristics of the tight sandstone samples in the Xu-3 section. Nuclear magnetic resonance technology is applied to plan gas–water injection simulation experiments, and the dynamic changes in pore water and gas content during the natural gas injection of tight reservoir rock samples are characterized. The main controlling factors are analyzed based on the theory of nuclear magnetic resonance singlet and multifractal models. The results showed that material composition, pore type, structural characteristics, and physical properties cooperatively control the charging characteristics of natural gas. There was no significant difference in mineral content among the tight sandstone samples, and the pore morphology types were mainly parallel plate-like pores and fracture-type pores. There were significant differences in the pore structure characteristics of the samples with varying burial depths. The heterogeneity of gas-bearing pores is negatively related to the buried depth of tight sandstone, is a coupling relationship with quartz and feldspar content, and is negatively correlated with pore permeability. The stronger the sample heterogeneity, the more unfavorable it is for natural gas migration and accumulation.
Study on the Seepage Model of Three-Dimensional Vertical Well Based on the Boundary Element Method
Authors: Wang Jialin , Ren Zongxiao , Liu Xinwei , Han Jinliang , Fan Zhaoyang , Zhao Hui
Published: December 2024

As one of the main numerical methods, the boundary element method boasts the advantages of fast computation speed and high accuracy. Based on the considerations of the influence of pressure drop, perforation height, skin coefficient, reservoir coefficient, and reservoir radius on the seepage law, a novel three-dimensional seepage model for vertical wells was established using the Laplace transform method and Stehfest numerical inversion method. The model was utilized to examine the velocity of pressure propagation and drop amplitude, revealing that the near-well area experienced faster propagation and drop than the far-well area. During dimensional analysis, it was observed that neglecting the effects of formation pressure change could lead to a substantial increase in the dimensional error of bottom hole pressure, with a maximum error of 9.45% recorded in this study. Additionally, a sensitivity analysis was conducted on perforation length, wellbore reservoir coefficient, skin coefficient, and reservoir radius to further elucidate the seepage law of vertical wells. This study provides theoretical guidance for oil and gas production. The original contribution of this research lies in the incorporation of formation pressure changes into the three-dimensional seepage model of vertical wells for the first time, which significantly enhances the model’s accuracy and practicality.
Difficult Diagnosis of Spontaneous Intracranial Hypotension with Nausea and Lower Abdominal Pain as Main Complaints: A Case Report
Authors: Yokoi Misaki , Kenzaka Tsuneaki , Asano Mari , Sugimoto Ryu , Nishisaki Hogara
Published: December 2024

Background and Clinical Significance: Symptoms of spontaneous intracranial hypotension include orthostatic headaches due to decreased cerebrospinal fluid (CSF) levels. Here, we present a 24-year-old female admitted to an obstetrics and gynecology department with primary complaints of lower abdominal pain and dysmenorrhea with subsequent diagnosis of spontaneous intracranial hypotension (SIH). Case Presentation: The patient had experienced nausea and lower abdominal pain independent of her menstrual cycle 5 days before admission, for which she visited the emergency department 3 days later. On admission, her symptoms were temporarily relieved by administering analgesics; thus, she was discharged. However, later, the symptoms worsened. Consequently, she returned to the emergency department for further evaluation, including blood tests, imaging, and endoscopy, which revealed no nausea- or abdominal pain-related organic abnormalities. On day 10, she developed a headache, aggravated by lying in the supine position and improved by sitting. Additional history revealed a diagnosis of SIH owing to the worsening abdominal pain in the supine position. An 111In CSF cavity scintigram showed no spinal fluid leakage; early intrabladder radioisotope (RI) accumulation was observed, and the residual 24 h CSF cavity RI was >30%. At a referral specialist hospital, an epidural saline infusion test was performed, which improved her headache and lower abdominal pain. Blood patch therapy improved her lower abdominal pain, headache, and dysmenorrhea. Conclusions: The final diagnosis was SIH, with symptoms attributed to CSF depletion. The patient also experienced rare paradoxical postural-related headaches and lower abdominal pain, aggravated by lying in the supine position, contributing to the final diagnosis.
A Multi-Parameter Calibration Method Based on the Newton Method and the Genetic Algorithm in Airborne Array Synthetic Aperture Radar
Authors: Wang Dawei , Li Zhenhua , Zhang Fubo , Chen Longyong
Published: December 2024

Airborne array synthetic aperture radar (SAR) can achieve three-dimensional (3D) imaging of the observed scene in a single flight. Nevertheless, the imaging process of airborne array SAR is subject to various parameter errors due to unstable factors. Such errors degrade the quality of 3D imaging, particularly for the elevation imaging results, which necessitates the employment of super-resolution algorithms. The most significant error parameters include the amplitude and phase imbalances between multiple channels, as well as the phase-center positions of each channel. Owing to the coupled nature of these parameter errors, the calibration accuracy for each parameter independently is relatively sub-par, while super-resolution algorithms have strict demands for parameter precision. Addressing these challenges, this article proposes a multi-parameter calibration method for airborne array SAR based on the Newton method and the genetic algorithm. Initially, a least squares model for multi-parameter calibration is established, followed by leveraging the global optimization characteristics of genetic algorithms and the rapid convergence property of the Newton method. The genetic algorithm is utilized to locate a sub-optimal solution in proximity to the optimal one, subsequently converging swiftly to the optimal solution via the Newton method, which incorporates second-order information. This approach averts the pitfalls of local convergence due to large initial value errors, thereby enhancing the algorithm’s robustness. The proposed method effectively enhances the precision of multi-parameter calibration, which is of significant importance in ensuring the quality of 3D imaging of airborne array SAR.
Multipath Mitigation in Single-Frequency Multi-GNSS Tightly Combined Positioning via a Modified Multipath Hemispherical Map Method
Authors: Tao Yuan , Liu Chao , Tong Runfa , Zhao Xingwang , Feng Yong , Wang Jian
Published: December 2024

Multipath is a source of error that limits the Global Navigation Satellite System (GNSS) positioning precision in short baselines. The tightly combined model between systems increases the number of observations and enhances the strength of the mathematical model owing to the continuous improvement in GNSS. Multipath mitigation of the multi-GNSS tightly combined model can improve the positioning precision in complex environments. Interoperability of the multipath hemispherical map (MHM) models of different systems can enhance the performance of the MHM model due to the small multipath differences in single overlapping frequencies. The adoption of advanced sidereal filtering (ASF) to model the multipath for each satellite brings computational challenges owing to the characteristics of the multi-constellation heterogeneity of different systems; the balance efficiency and precision become the key issues affecting the performance of the MHM model owing to the sparse characteristics of the satellite distribution. Therefore, we propose a modified MHM method to mitigate the multipath for single-frequency multi-GNSS tightly combined positioning. The method divides the hemispherical map into 36 × 9 grids at 10° × 10° resolution and then searches with the elevation angle and azimuth angle as independent variables to obtain the multipath value of the nearest point. We used the k-d tree to improve the search efficiency without affecting precision. Experiments show that the proposed method improves the mean precision over ASF by 10.20%, 10.77%, and 9.29% for GPS, BDS, and Galileo satellite single-difference residuals, respectively. The precision improvements of the modified MHM in the E, N, and U directions were 32.82%, 40.65%, and 31.97%, respectively. The modified MHM exhibits greater performance and behaves more consistently.
Blind Infrared Remote-Sensing Image Deblurring Algorithm via Edge Composite-Gradient Feature Prior and Detail Maintenance
Authors: Zhao Xiaohang , Li Mingxuan , Nie Ting , Han Chengshan , Huang Liang
Published: December 2024

The problem of blind image deblurring remains a challenging inverse problem, due to the ill-posed nature of estimating unknown blur kernels and latent images within the Maximum A Posteriori (MAP) framework. To address this challenge, traditional methods often rely on sparse regularization priors to mitigate the uncertainty inherent in the problem. In this paper, we propose a novel blind deblurring model based on the MAP framework that leverages Composite-Gradient Feature (CGF) variations in edge regions after image blurring. This prior term is specifically designed to exploit the high sparsity of sharp edge regions in clear images, thereby effectively alleviating the ill-posedness of the problem. Unlike existing methods that focus on local gradient information, our approach focuses on the aggregation of edge regions, enabling better detection of both sharp and smoothed edges in blurred images. In the blur kernel estimation process, we enhance the accuracy of the kernel by assigning effective edge information from the blurred image to the smoothed intermediate latent image, preserving critical structural details lost during the blurring process. To further improve the edge-preserving restoration, we introduce an adaptive regularizer that outperforms traditional total variation regularization by better maintaining edge integrity in both clear and blurred images. The proposed variational model is efficiently implemented using alternating iterative techniques. Extensive numerical experiments and comparisons with state-of-the-art methods demonstrate the superior performance of our approach, highlighting its effectiveness and real-world applicability in diverse image-restoration tasks.
Rapid Classification of Unroasted Green Coffee Beans and Spices Based on the Tentative Determination of Volatile Compounds by Solid-Phase Dynamic Extraction (SPDE) and Gas Chromatography–Mass Spectrometry (GC–MS) with Supervised Learning
Authors: Lazaridis Dimitrios G. , Kokkosi Evelyna K. , Mylonaki Emmanouela N. , Karabagias Vassilios K. , Andritsos Nikolaos D. , Karabagias Ioannis K.
Published: December 2024

The present study comprises the second part of our previous work that dealt mainly with the phytochemical and physicochemical characterization of commercial unroasted green coffee beans, clove, cinnamon–clove and nutmeg ethanolic extracts of grape origin. In the present study, we focused on producing a discriminating model concerning commercial unroasted green coffee beans, clove, cinnamon, cinnamon and clove mixture (1:1, w/w), and nutmeg fine powders based on multivariate analysis of variance and supervised learning from tentative data of volatile compounds analysis, carried out with solid phase dynamic extraction in combination with gas chromatography–mass spectrometry. Results showed that 7 volatile compounds, i.e., ethylene, methanol, 3-methylpentane, ethyl acetate, 9-hexadecen-1-ol, toluene, and methyl acetate, could differentiate the investigated samples resulting in a 100% classification rate using the cross-validation method of linear discriminant analysis. Results were further confirmed using partial least squares regression analysis. The study contributes to the typification of commercial unroasted green coffee beans, cinnamon, clove, cinnamon and clove mixture, and nutmeg, based on selected volatile compounds. In addition, the study provides further support to the literature by means of a possible substitution of these products in rapid analysis tests, given the statistical models developed.
Korean American Immigrant Women’s Mammography Use in Korea: Factors Associated with Medical Tourism
Authors: Lee Mi Hwa , Merighi Joseph , Cofie Leslie , Rogers Bryan
Published: December 2024

This study examined social determinants associated with Korean American immigrant women’s mammography use in Korea after immigration to the United States. Data from a cross-sectional survey were obtained from 187 women in Los Angeles County, California. More than one-quarter (28.3%) of the respondents reported returning to Korea for a mammogram after immigrating to the United States. Multivariable logistic regression revealed that compared to those who had their first mammogram in Korea, Korean American immigrant women who had their first mammogram in the United States were less likely to return to Korea for subsequent screenings (AOR = 0.02, 95% CI: <0.001, 0.05); also, those who had employer-based health insurance in the United States were less likely to get a mammogram in Korea after immigration (AOR = 0.01, 95% CI: <0.01, 0.18). Findings suggest that women familiar with the Korean healthcare system and who are uninsured or have inconsistent healthcare coverage in the United States may seek care in Korea. To promote adherence to breast cancer screening guidelines among Korean American immigrant women residing in the United States, greater access to free or low-cost screening services and breast cancer screening education is warranted to reduce the risk of later stage breast cancer detection resulting from medical tourism.
Understanding Emission Trends, Regional Distribution Differences, and Synergistic Emission Effects in the Transportation Sector in Terms of Social Factors and Energy Consumption
Authors: Zhao Yu , Divigalpitiya Prasanna
Published: December 2024

China’s transportation sector plays a significant role in reducing carbon dioxide (CO2) and air pollution. Previous studies have predominantly utilized scenario analysis to forecast emissions for the next 30 to 50 years based on coefficients from a base year. To elucidate the current state of gas emissions in the transportation sector, this study employed panel data for 10 types of gas emissions from 2001 to 2020, analyzing their emission characteristics, tendencies, and synergistic effects. Utilizing the Kaya equation and the logarithmic mean division index (LMDI) decomposition method, we developed a model of pollutant emissions that considers the synergistic effects, pollution emission intensity, energy mix, energy consumption intensity, and population. The results show that all pollutants in the transportation sector decreased except for NH3 and CO2. There was a synergistic effect between air pollutants and CO2 emissions, but the reduction was not significant. From 2013 to 2020, the transportation sector shifted from a high emission intensity with low synergy to a low emission intensity with high synergy. The results indicate that off-road mobile vehicles, on-road diesel vehicles, and motorcycles became the main source of emissions from transportation in certain provinces, and a key area requiring attention in policy development. Gasoline consumption was identified as the primary contributor to the significant increase in synergistic emission variability in the transportation sector. These results provide policymakers with practical ways to optimize emission reduction pathways.
How Does Management Control Affect New Product Development Performance? A Research Methodology with OLS and fsQCA
Authors: Li Xingteng , Chen Yue-e
Published: December 2024

High-quality development has become one of the important goals pursued by Chinese enterprises at present, and innovation is an important channel to realize high-quality development. Effective collaboration stands out as a pivotal element for the success of new product development (NPD). There are a variety of control mechanisms applied to mitigate uncertainty and foster cooperation. Despite the importance of these controls, the interplay between formal and informal management controls in NPD has been underexplored in prior research. The goal of this study is to validate the relationship between formal and informal control in a new product development scenario, responding to the debate about whether there is a substitution effect or a complementary effect between the two. This study addresses this gap by initially employing ordinary least squares (OLS) regression analysis to examine the role of each management control. Subsequently, fuzzy set qualitative comparative analysis (fsQCA) is employed to identify strategies for achieving high NPD performance in Chinese manufacturing enterprises. The results from the OLS analysis demonstrate that all forms of management control, especially trust, are effective in the improvement of NPD performance, while the results from fsQCA confirm that there is a complementary effect between formal and informal control, suggesting that informal control cannot function well without formal control. This research illuminates the synergistic dynamics of management controls within an open innovation context and emphasizes the importance of integrating both formal and informal controls to optimize NPD performance.
The Impact of Agricultural Cooperatives on Farmers’ Agricultural Revenue: Evidence from Rural China
Authors: He Yuanqian , Chen Yiting
Published: December 2024

Farmer’s incentive is a core issue in achieving sustainable agricultural development. In many developing countries, smallholder farming is predominant in agricultural production, potentially limiting improvements in agricultural sustainability. Promoting agricultural cooperatives is a widely adopted strategy to help resource-poor farmers obtain higher agricultural revenue. In China, these organizations have expanded rapidly since the early 21st century, reaching 2.22 million by September 2023 and providing services to nearly half of farming households. However, their effectiveness and impact on enhancing agricultural revenue remain subjects of ongoing debate. To provide more empirical evidence on this topic, this paper constructs an agricultural cooperatives database based on the national commercial registration enterprise dataset and matches it with the National Fixed Point Rural Survey (NFP). The findings reveal that the development of agricultural cooperatives in China significantly helps farmers enhance their production revenue, leading to an increase in household income. Furthermore, the paper identifies strong heterogeneity in the positive effects of cooperative development at both the village and household levels. In the mechanism analysis, it is shown that agricultural cooperatives in China facilitate increased investment in capital, intermediate inputs, and technology, optimizing the allocation of production factors in agricultural processes, thereby improving land productivity and ultimately increasing agricultural revenue.