bluuebunny/crossref_metadata_2025 huggingface dataset:
A Normal Mode Model Based on the Spectral Element Method for Simulating Horizontally Layered Acoustic Waveguides
Authors: Zhang Yinuo , Tu Houwang , Wang Yongxian , Xu Guojun , Gao Dongbao
Published: August 2024

Acoustic waves are essential tools for guiding underwater activities. For many years, numerical modeling of ocean acoustic propagation has been a major research focus in underwater acoustics. Normal mode theory, one of the earliest and most extensively studied methods in this field, is renowned for its well-established theoretical framework. The core of normal mode theory involves the numerical solution of modal equations. In classical normal mode models, these equations are typically discretized using low-order finite difference methods, which, while broadly applicable, suffer from a limited convergence rate. The spectral element method, widely used in the seismic field, is recognized for its spectral precision and flexibility. In this article, we propose a normal mode model discretized using the spectral element method. The weak form of the modal equation directly satisfies boundary and interface conditions without requiring additional operations. The entire computational domain can be divided into segments of varying number and length, configured according to environmental conditions. The perfectly matched layer technique is employed to simulate acoustic half-space boundary conditions, effectively addressing the high computational costs and numerical instability associated with traditional artificial absorbing layers. Based on these algorithms, we have developed a numerical program (SEM). This research verifies the accuracy of the spectral element model through three different types of numerical experiments.
Endometrial E-cadherin and N-cadherin Expression during the Mid-Secretory Phase of Women with Ovarian Endometrioma or Uterine Fibroids
Authors: Yun Bo Seong , Yun Na Yeon , Lee Jung Eun , Go Minyeon , Jang Hee Yeon , Park Ji Eun , Roh Ju-Won , Shim Sung Shin
Published: August 2024

Background: Endometriosis and uterine fibroids are benign conditions frequently linked to subfertility/infertility. Recent research has highlighted the importance of epithelial–mesenchymal transition between embryonic and endometrial cells in the context of embryo implantation. Additionally, the adverse endometrial environment during implantation has been proposed as a mechanism contributing to infertility in endometriosis. Nevertheless, the role of cadherin molecule alterations in relation to endometrial receptivity and embryo invasion remains a subject of controversy. Methods: We investigated the expression patterns of E-cadherin and N-cadherin in the endometria of women with ovarian endometrioma or uterine fibroids and assessed whether they differed from those of healthy women. We enrolled 17 women with ovarian endometrioma, 16 with uterine fibroids, and 6 healthy women. Endometrial tissues were obtained at the mid-secretory phase on days 19–24 of the menstrual cycle. The E-cadherin and N-cadherin mRNA and protein expression levels were measured using quantitative reverse transcriptase polymerase chain reaction and Western blot analysis, respectively. Results: The E-cadherin and N-cadherin mRNA expression levels were higher and lower, respectively, in the endometrium of women with ovarian endometrioma than in those of the controls. In the endometrium of women with uterine fibroids, similar patterns with higher E-cadherin and lower N-cadherin levels were observed compared with that of the controls. Protein expression showed similar patterns. Conclusions: Our findings revealed higher E-cadherin expression and lower N-cadherin expression in the endometria of women with infertility-related diseases than in those of healthy women in the mid-secretory phase. This suggests a resistance to endometrial receptivity, potentially reflecting mesenchymal–epithelial transition properties.
Machine Learning for the Identification of Key Predictors to Bayley Outcomes: A Preterm Cohort Study
Authors: Grđan Stevanović Petra , Barišić Nina , Šunić Iva , Malby Schoos Ann-Marie , Bunoza Branka , Grizelj Ruža , Bogdanić Ana , Jovanović Ivan , Lovrić Mario
Published: August 2024

Background: The aim of this study was to understand how neurological development of preterm infants can be predicted at earlier stages and explore the possibility of applying personalized approaches. Methods: Our study included a cohort of 64 preterm infants, between 24 and 34 weeks of gestation. Linear and nonlinear models were used to evaluate feature predictability to Bayley outcomes at the corrected age of 2 years. The outcomes were classified into motor, language, cognitive, and socio-emotional categories. Pediatricians’ opinions about the predictability of the same features were compared with machine learning. Results: According to our linear analysis sepsis, brain MRI findings and Apgar score at 5th minute were predictive for cognitive, Amiel-Tison neurological assessment at 12 months of corrected age for motor, while sepsis was predictive for socio-emotional outcome. None of the features were predictive for language outcome. Based on the machine learning analysis, sepsis was the key predictor for cognitive and motor outcome. For language outcome, gestational age, duration of hospitalization, and Apgar score at 5th minute were predictive, while for socio-emotional, gestational age, sepsis, and duration of hospitalization were predictive. Pediatricians’ opinions were that cardiopulmonary resuscitation is the key predictor for cognitive, motor, and socio-emotional, but gestational age for language outcome. Conclusions: The application of machine learning in predicting neurodevelopmental outcomes of preterm infants represents a significant advancement in neonatal care. The integration of machine learning models with clinical workflows requires ongoing education and collaboration between data scientists and healthcare professionals to ensure the models’ practical applicability and interpretability.
Landscape Character Assessment (LCA) in Historic Coal Mining Settings for Landscape Conservation: A Systematic Review
Authors: Liu Qi , Zainal Abidin Nor Arbina , Maliki Nor Zarifah , Zhang Kailai , Li Zhi , Liu Sha
Published: August 2024

Landscape character assessment (LCA) is a crucial tool for conserving an area’s unique character. However, in our literature review, we found no data linking LCA to historic coal mining settings. This systematic review explores the ways in which the landscape character assessment (LCA) methodology has been applied, as well as the factors that influence it, in the conservation of historic coal mine landscapes. It focuses on three areas: analyzing the ways in which LCA has been applied in landscape conservation, proposing recommendations for the application of LCA in historic coal mine setting landscapes, and summarizing the factors that influence LCA in landscape conservation in historic coal mine settings. Methods: This study used the Meta-Analyses (PRISMA) method to perform the systematic review. The whole review was selected from 2030 potential articles; a total of 21 articles were included. Results: This study demonstrates that the LCA approach can be operationalized in the conservation of environmental landscapes in historic coal mines by combining cluster analysis and multi-scale assessment and incorporating other theories. The quality of the results can be affected by factors such as the accuracy and completeness of the data and the complexity and tractability of the model. Conclusions: Future research should focus on improving the data capture technology, model complexity, and design of actionable models. Additionally, we recommend the strategies of enhancing stakeholder engagement and raising public awareness.
Effects of Electrochemical Hydrogen Charging Parameters on the Mechanical Behaviors of High-Strength Steel
Authors: Dan Wen-Jiao , Shi Hao , Tang Cheng-Wang , Wang Xu-Yang
Published: August 2024

Extended exposure to seawater results in the erosion of the structural high-strength steels utilized in marine equipment, primarily due to the infiltration of hydrogen. Consequently, this erosion leads to a decrease in the mechanical properties of the material. In this investigation, the mechanical responses of Q690 structural high-strength steel specimens were investigated by considering various hydrogen charging parameters, such as the current density, charging duration, and solution concentration values. The findings highlighted the significant impacts of electrochemical hydrogen charging parameters on the mechanical behaviors of Q690 steel samples. Specifically, a linear relationship was observed between the mechanical properties and the hydrogen charging current densities, while the associations with the charging duration and solution concentration were nonlinear. Additionally, the fracture morphology under various hydrogen charging parameters was analyzed and discussed. The results demonstrate that the mechanical properties of the material degrade with increasing hydrogen charging parameters, with tensile strength and yield stress decreasing by approximately 2–4%, and elongation after fracture reducing by about 20%. The findings also reveal that macroscopic fractures exhibit significant necking in uncharged conditions. As hydrogen charging parameters increase, macroscopic necking gradually diminishes, the number of microscopic dimples decreases, and the material ultimately transitions to a fully brittle fracture.
Lithiophilic Reduced Graphene Oxide/Carbonized Zeolite Imidazolate Framework-8 Composite Host for Stable Li Metal Anodes
Authors: Jeong Sang-Won , Oh Byeong Il , Chang Eun Seo , Park Jeong-Ann , Kim Hyun-Kyung
Published: August 2024

Lithium (Li) metal is regarded as a next-generation anode material owing to its high energy density. However, issues such as dendritic growth and volume changes during charging and discharging pose significant challenges for commercialization. We propose using lithiophilic reduced graphene oxide (rGO) and carbonized zeolite imidazolate framework-8 (C-ZIF-8) composites as host materials for Li to address these problems. The rGO/C-ZIF-8 composites are synthesized through a simple redox reaction followed by carbonization and are characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM), and X-ray photoelectron spectroscopy (XPS). The roles of chemical composition, characteristics, and morphology are demonstrated. As a result of these favorable structural and functional properties, the Li symmetric cell with rGO/C-ZIF-8 exhibits a stable voltage profile for more than 100 h at 1 mA cm−2 without short-circuiting. A relatively low Li plating/stripping overpotential of ~101.5 mV at a high current density of 10 mA cm−2 is confirmed. Moreover, a rGO/C-ZIF-8-Li full cell paired with a LiFePO4 cathode demonstrates good cyclability and rate capability.
Research Progress on Laser Powder Bed Fusion Additive Manufacturing of Zinc Alloys
Authors: Meng Fuxiang , Du Yulei
Published: August 2024

Zinc, along with magnesium and iron, is considered one of the most promising biodegradable metals. Compared with magnesium and iron, pure Zn exhibits poor mechanical properties, despite its mild biological corrosion behavior and beneficial biocompatibility. Laser powder bed fusion (LPBF), unlike traditional manufacturing techniques, has the capability to rapidly manufacture near-net-shape components. At present, although the combination of LPBF and Zn has made great progress, it is still in its infancy. Element loss and porosity are common processing problems for LPBF Zn, mainly due to evaporation during melting under a high-energy beam. The formation quality and properties of the final material are closely related to the alloy composition, design and processing. This work reviews the state of research and future perspective on LPBF zinc from comprehensive assessments such as powder characteristics, alloy composition, processing, formation quality, microstructure, and properties. The effects of powder characteristics, process parameters and evaporation on formation quality are introduced. The mechanical, corrosion, and biocompatibility properties of LPBF Zn and their test methodologies are introduced. The effects of microstructure on mechanical properties and corrosion properties are analyzed in detail. The practical medical application of Zn is introduced. Finally, current research status is summarized together with suggested directions for advancing knowledge about LPBF Zn.
Waste Symbiosis through the Synthesis of Highly Crystalline LTA and SOD Zeolites
Authors: Ritter Magali Teresinha , Padilla Isabel , Lobo-Recio María Ángeles , Romero Maximina , López-Delgado Aurora
Published: August 2024

In recent years, the demand for natural and synthetic zeolites has surged due to their distinctive properties and myriad industrial applications. This research aims to synthesise crystalline zeolites by co-recycling two industrial wastes: salt slag (SS) and rice husk ash (RHA). Salt slag, a problematic by-product of secondary aluminium smelting, is classified as hazardous waste due to its reactive and leachable nature, though it is rich in aluminium. Conversely, RHA, an abundant and cost-effective by-product of the agro-food sector, boasts a high silicon content. These wastes were utilised as aluminium and silicon sources for synthesising various zeolites. This study examined the effects of temperature, ageing time, and sodium concentration on the formation of different zeolite phases and their crystallinity. Results indicated that increased Na+ concentration favoured sodalite (SOD) zeolite formation, whereas Linde type–A (LTA) zeolite formation was promoted at higher temperatures and extended ageing times. The formation range of the different zeolites was defined and supported by crystallographic, microstructural, and morphological analyses. Additionally, the thermal behaviour of the zeolites was investigated. This work underscores the potential to transform industrial waste, including hazardous materials like salt slag, into sustainable, high-value materials, fostering efficient waste co-recycling and promoting clean, sustainable industrial production through cross-sectoral industrial symbiosis.
Influence of Defects and Microstructure on the Thermal Expansion Behavior and the Mechanical Properties of Additively Manufactured Fe-36Ni
Authors: Kahlert Moritz , Wegener Thomas , Laabs Leonard , Vollmer Malte , Niendorf Thomas
Published: August 2024

Laser-based powder bed fusion of metals (PBF-LB/M) is a widely used additive manufacturing process characterized by a high degree of design freedom. As a result, near fully dense complex components can be produced in near-net shape by PBF-LB/M. Recently, the PBF-LB/M process was found to be a promising candidate to overcome challenges related to conventional machining of the Fe64Ni36 Invar alloy being well known for a low coefficient of thermal expansion (CTE). In this context, a correlation between process-induced porosity and the CTE was presumed in several studies. Therefore, the present study investigates whether the unique thermal properties of the PBF-LB/M-processed Fe64Ni36 Invar alloy can be tailored by the selective integration of defects. For this purpose, a full-factorial experimental design, representing by far the largest processing window in the literature, was considered, correlating the thermal expansion properties with porosity and hardness. Furthermore, the microstructure and mechanical properties were investigated by scanning electron microscopy and quasi-static tensile tests. Results by means of statistical analysis reveal that a systematic correlation between porosity and CTE properties could not be determined. However, by using specific process parameter combinations, the microstructure changed from a fine-grained fan-like structure to a coarse columnar structure.
Weak Signal Extraction in Noise Using Variable-Step Gaussian-Sinusiodal Filter
Authors: Lou Haiyang , Hao Rujiang , Zhang Jianchao
Published: August 2024

When analyzing vibration or acoustic signals in machinery, noise interference within the characteristic signals can significantly distort the results. This issue is particularly pronounced in complex environments, where mechanical signals are often overwhelmed by noise, making it extremely difficult or even impossible to determine the operational status of mechanical equipment by the analysis of characteristic signals. Existing methods for analyzing weak signals in the presence of strong Gaussian noise have limitations in their effectiveness. This paper proposes an innovative approach that utilizes a Variable-Step Gaussian-Sinusoidal Filter (VSGF) combined with rotational coordinate transformation to extract weak signals from strong noise backgrounds. The proposed method improves noise reduction capabilities and frequency selectivity, showing significant improvements over traditional Gaussian filters. Experimental validation demonstrates that the signal detection accuracy of the proposed method is 10–15% higher than that of conventional Gaussian filters. This paper presents a detailed mathematical analysis, experimental validation, and comparisons with other methods to demonstrate the effectiveness of the proposed approach.
An Irregular Pupil Localization Network Driven by ResNet Architecture
Authors: Yang Genjian , Chen Wenbai , Wu Peiliang , Gou Jianping , Meng Xintong
Published: August 2024

The precise and robust localization of pupils is crucial for advancing medical diagnostics and enhancing user experience. Currently, the predominant method for determining the center of the pupil relies on the principles of multi-view geometry, necessitating the simultaneous operation of multiple sensors at different angles. This study introduces a single-stage pupil localization network named ResDenseDilateNet, which is aimed at utilizing a single sensor for pupil localization and ensuring accuracy and stability across various application environments. Our network utilizes near-infrared (NIR) imaging to ensure high-quality image output, meeting the demands of most current applications. A unique technical highlight is the seamless integration of the efficient characteristics of the Deep Residual Network (ResNet) with the Dense Dilated Convolutions Merging Module (DDCM), which substantially enhances the network’s performance in precisely capturing pupil features, providing a deep and accurate understanding and extraction of pupil details. This innovative combination strategy greatly improves the system’s ability to handle the complexity and subtleties of pupil detection, as well as its adaptability to dynamic pupil changes and environmental factors. Furthermore, we have proposed an innovative loss function, the Contour Centering Loss, which is specifically designed for irregular or partially occluded pupil scenarios. This method innovatively calculates the pupil center point, significantly enhancing the accuracy of pupil localization and robustness of the model in dealing with varied pupil morphologies and partial occlusions. The technology presented in this study not only significantly improves the precision of pupil localization but also exhibits exceptional adaptability and robustness in dealing with complex scenarios, diverse pupil shapes, and occlusions, laying a solid foundation for the future development and application of pupil localization technology.
Quantifying Wildlife Abundance: Negative Rayleigh Modeling of Line Transect Data
Authors: Almarashi Abdullah M.
Published: August 2024

This study introduces a negative Rayleigh detection model for estimating population abundance in line transect surveys. The model satisfies key detection conditions and provides a detailed analysis of its probability density function, moments, and other essential characteristics. Parameters are estimated using three methods: moment estimator, maximum likelihood estimator, and Bayesian estimator. The model’s performance is evaluated through simulations, comparing its estimators to those from established models. An empirical application using perpendicular distance data further assesses the model, with goodness-of-fit statistics demonstrating its advantages over traditional methods.
An Empirical Investigation on the Visual Imagery of Augmented Reality User Interfaces for Smart Electric Vehicles Based on Kansei Engineering and FAHP-GRA
Authors: Lin Jin-Long , Zheng Meng-Cong
Published: August 2024

Smart electric vehicles (SEVs) hold significant potential in alleviating the energy crisis and environmental pollution. The augmented reality (AR) dashboard, a key feature of SEVs, is attracting considerable attention due to its ability to enhance driving safety and user experience through real-time, intuitive driving information. This study innovatively integrates Kansei engineering, factor analysis, fuzzy systems theory, analytic hierarchy process, grey relational analysis, and factorial experimentation to evaluate AR dashboards’ visual imagery and subjective preferences. The findings reveal that designs featuring blue planar and unconventional-shaped dials exhibit the best performance in terms of visual imagery. Subsequent factorial experiments confirmed these results, showing that drivers most favor blue-dominant designs. Furthermore, in unconventional-shaped dial designs, the visual effect of vertical 3D is more popular with drivers than horizontal 3D, while the opposite is true in round dials. This study provides a scientific evaluation method for assessing the emotional experience of AR dashboard interfaces. Additionally, these findings will help reduce the subjectivity in interface design and enhance the overall competitiveness of SEV vehicles.
Assessing Climate Transition Risks in the Colombian Processed Food Sector: A Fuzzy Logic and Multi-Criteria Decision-Making Approach
Authors: Pérez-Pérez Juan F. , Gómez Pablo Isaza , Bonet Isis , Sánchez-Pinzón María Solange , Caraffini Fabio , Lochmuller Christian
Published: August 2024

Climate risk assessment is critical for organisations, especially in sectors such as the processed food sector in Colombia. This study addresses the identification and assessment of the main climate transition risks using an approach that combines fuzzy logic with several multi-criteria decision-making methods. This approach makes it possible to handle the inherent imprecision of these risks and to use linguistic expressions to better describe them. The results indicate that the most critical risks are price volatility and availability of raw materials, the shift towards less carbon-intensive production models, increased carbon taxes, technological advances, and associated development or implementation costs. These risks are the most significant for the organisation studied and underline the need for investments to meet regulatory requirements, which are the main financial drivers for organisations. This analysis highlights the importance of a robust framework to anticipate and mitigate the impacts of the climate transition.
KCB-FLAT: Enhancing Chinese Named Entity Recognition with Syntactic Information and Boundary Smoothing Techniques
Authors: Deng Zhenrong , Huang Zheng , Wei Shiwei , Zhang Jinglin
Published: August 2024

Named entity recognition (NER) is a fundamental task in Natural Language Processing (NLP). During the training process, NER models suffer from over-confidence, and especially for the Chinese NER task, it involves word segmentation and introduces erroneous entity boundary segmentation, exacerbating over-confidence and reducing the model’s overall performance. These issues limit further enhancement of NER models. To tackle these problems, we proposes a new model named KCB-FLAT, designed to enhance Chinese NER performance by integrating enriched semantic information with the word-Boundary Smoothing technique. Particularly, we first extract various types of syntactic data and utilize a network named Key-Value Memory Network, based on syntactic information to functionalize this, integrating it through an attention mechanism to generate syntactic feature embeddings for Chinese characters. Subsequently, we employed an encoder named Cross-Transformer to thoroughly combine syntactic and lexical information to address the entity boundary segmentation errors caused by lexical information. Finally, we introduce a Boundary Smoothing module, combined with a regularity-conscious function, to capture the internal regularity of per entity, reducing the model’s overconfidence in entity probabilities through smoothing. Experimental results demonstrate that the proposed model achieves exceptional performance on the MSRA, Resume, Weibo, and self-built ZJ datasets, as verified by the F1 score.
Ameliorative Effect of Chitosan/Spirulina platensis Ethanolic Extract Nanoformulation against Cyclophosphamide-Induced Ovarian Toxicity: Role of PPAR-γ/Nrf-2/HO-1 and NF-kB/TNF-α Signaling Pathways
Authors: Almukainzi May , El-Masry Thanaa A. , Ibrahim Hanaa A. , Saad Hebatallah M. , El Zahaby Enas I. , Saleh Asmaa , El-Nagar Maysa M. F.
Published: August 2024

Cyclophosphamide (CP) is an anticancer drug that causes infertility disorders. This study was designed to evaluate a nanoformulation of chitosan with an ethanolic extract from Spirulina platensis in terms of its protection against cyclophosphamide-induced ovarian toxicity. Nine groups of female Wistar rats were randomly assigned as follows: 1: control vehicle, 2: chitosan polymer, 3: telmisartan, 4: Spirulina platensis extract, 5: nanoformulation of the Spirulina platensis, and 6: single injection of CP; groups 7, 8, and 9 received the same treatments as those used in groups 3, 4, and 5, respectively, with a single dose of CP (200 mg/kg, I.P). The results displayed that the CP treatment decreased estradiol, progesterone, anti-mullerian hormone, and GSH content, and it downregulated PPAR-γ, Nrf-2, and HO-1 gene expression. In addition, the CP treatment caused an increase in the FSH, LH, and MDA levels. In the same manner, the protein expression of caspase-3, NF-kB, and TNF-α was upregulated in response to the CP treatment, while PPAR-γ was downregulated in comparison with the control. The rats treated with SPNPs exhibited a substantial reduction in the detrimental effects of oxidative stress and inflammation of the ovarian tissue. This study’s conclusions showed that SPNPs counteracted the effects of CP, preventing the death of ovarian follicles and restoring the gonadotropin hormone balance and normal ovarian histological appearance.
Flow Dynamics through a High Swelling Nanofiber Membrane Processed at Different Relative Humidities: A Study on a FexOy/Polyvinyl Alcohol Composite
Authors: Santos Ayelen C. , Vergara-Rubio Alicia , Mazocca Angel J. , Goyanes Silvia
Published: August 2024

Addressing the global problem of polluted water requires sustainable, efficient, and scalable remediation solutions, such as electrospun polyvinyl alcohol (PVA) membranes incorporating specific nanoadsorbents. The retention of contaminants depends on membrane swelling, morphology, and the adsorbent within the nanofiber. This study investigated the effect of relative humidity (RH) within the electrospinning chamber on the morphology of the resulting mats and how this affected the flow dynamics depending on whether or not the permeating liquid induced swelling in the membranes. An insolubilized PVA membrane was used as a hydrophilic filter model and a PVA membrane filled with iron oxide nanoparticles (IONPs) as a composite model (PVA + IONPs). The presence of IONPs increases the nanofiber diameter, which decreases when prepared under intermediate RH (IRH). Consequently, the nanofiber configuration, which is critical for filtration tortuosity, is influenced by RH. The initial swelling results in over 60% greater water flux through PVA + IONPs compared to PVA at an equivalent RH. This characterization helps to optimize membrane applications, highlighting that PVA + IONPs exhibit lower permeability values at IRH, indicating improved contaminant retention capabilities.
Fatigue Response of Additive-Manufactured 316L Stainless Steel
Authors: Chepkoech Melody , Omoniyi Peter , Owolabi Gbadebo
Published: August 2024

This study investigated the fatigue performance of 316L stainless steel fabricated via laser powder bed fusion (LPBF). Stress-controlled fatigue tests were performed at different stress amplitudes on vertically built samples using a frequency of 15 Hz and a stress ratio of 0.1. The stress amplitudes were varied to provide the cyclic response of the materials under a range of loading conditions. The average fatigue strength was determined to be 92.94 MPa, corresponding to a maximum stress of 185.87 MPa. The microstructures were observed through scanning electron microscopy (SEM) with the aid of electron backscattered diffraction (EBSD), and the average grain size of the as-built samples was determined to be 15.6 µm, with most grains having a <110> preferred crystallographic orientation. A higher kernel average misorientation value was measured on the deformed surfaces, revealing the increased misorientation of the grains. Defects were observed on the fractured surfaces acting as crack initiators while deflecting the crack propagation paths. The fatigue failure mode for the LPBF 316L samples was ductile, as illustrated by the numerous dimples on fracture surfaces and fatigue striations.
Editorial for the Special Issue on Sustainable Materials for Energy and Environmental Applications
Authors: Thirumurugan Arun , Kamaraj Sathish Kumar , Rednam Udayabhaskar , Raju Ramesh
Published: August 2024

Sustainable environmental management is an urgent problem that calls for innovative solutions to the problem of protecting and preserving the natural resources and ecosystems of the planet [...]
Electrical Properties and Reliability of AlGaN/GaN High Electron Mobility Transistor under RF Overdrive Stress at High Temperature
Authors: Liu Chang , Chen Yiqiang , Xie Yuhan , Liu Hongxia , Cai Zongqi
Published: August 2024

We have investigated the electrical properties and reliability of AlGaN/GaN high electron mobility transistors (HEMT) under high-temperature RF overdrive stress. The experimental results show that the drain current and transconductance of the device decrease at 25 °C and 55 °C but do not change significantly at 85 °C before and after the stress. The decline rate of the saturation drain current, the degradation amplitude of transconductance, and the drift amplitude of threshold voltage decrease with the increase in temperature. The results of pulse I–V and low-frequency noise tests show that the current collapse is inhibited, and the trap density is reduced at higher temperatures. The Electroluminescence (EL) test shows that the luminescence characteristics of the device after RF overdrive stress are more scattered and weaker. We believe that the degradation at lower temperatures is mainly due to the influence of the hot electron effect (HEE), while the change in electrical properties at higher temperatures is due to the weakening of HEE and the improvement of the Schottky interface.
Microscopic Processing of Transparent Material with Nanosecond and Ultrafast Lasers
Authors: Song Di , Wang Jiaqi , Wu Xinyang , Gao Liancong , Yang Jiao , Liu Xiaoxu , Luo Qing , Wang Dongdong , Wang You
Published: August 2024

Due to their excellent light transmission, heat resistance, corrosion resistance, high mechanical strength, and other characteristics, transparent materials have been widely used in emerging industries such as aviation, aerospace, microelectronics, interconnected communication, etc. Compared with the traditional mechanical processing and chemical processing of transparent materials, laser processing, with such characteristics as a high peak power, high energy density, and non-contact processing, has a lot of obvious advantages in processing efficiency and accuracy. In this paper, some of the recent research advancements concerning the laser processing of transparent materials are introduced in detail. Firstly, the basic mechanism of the interaction between the laser and material is briefly summarized on the time scale. The differences in principle between nanosecond, picosecond, and femtosecond pulse laser processing are analyzed. Then, the main technical means of the nanosecond laser processing of transparent materials are summarized. Next, the main application directions of the ultrafast laser processing of transparent materials are discussed, including the preparation of optical waveguide devices, periodic structure devices, micropores, and microchannels. Finally, this paper summarizes the prospects for the future development of laser processing transparent materials.
An Ultra-Low-Voltage Transconductance Stable and Enhanced OTA for ECG Signal Processing
Authors: Yin Yue , Zhang Xinbing , Feng Ziting , Qi Haobo , Lu Haodong , He Jiayu , Jin Chaoqi , Luo Yihao
Published: August 2024

In this paper, a rail-to-rail transconductance stable and enhanced ultra-low-voltage operational transconductance amplifier (OTA) is proposed for electrocardiogram (ECG) signal processing. The variation regularity of the bulk transconductance of pMOS and nMOS transistors and the cancellation mechanism of two types of transconductance variations are revealed. On this basis, a transconductance stabilization and enhancement technique is proposed. By using the “current-reused and transconductance-boosted complementary bulk-driven pseudo-differential pairs” structure, the bulk-driven pseudo-differential pair during the input common-mode range (ICMR) is stabilized and enhanced. The proposed OTA based on this technology is simulated using the TSMC 0.18 μm process in a Cadence environment. The proposed OTA consumes a power below 30 nW at a 0.4 V voltage supply with a DC gain of 54.9 dB and a gain-bandwidth product (GBW) of 14.4 kHz under a 15 pF capacitance load. The OTA has a high small signal figure-of-merit (FoM) of 7410 and excellent common-mode voltage (VCM) stability, with a transconductance variation of about 1.35%. Based on a current-scaling version of the proposed OTA, an OTA-C low-pass filter (LPF) for ECG signal processing with VCM stability is built and simulated. With a −3 dB bandwidth of 250 Hz and a power consumption of 20.23 nW, the filter achieves a FoM of 3.41 × 10−13, demonstrating good performance.
Moment Estimation from Time Domain Electromagnetic Data
Authors: Vallée Marc , Moussaoui Mouhamed
Published: August 2024

Moment representations have been proposed to facilitate the interpretation of geophysical time domain electromagnetic responses. We present a new methodology for estimating these moments from field data for different system waveforms when on-time and off-time measurements are available. Quadrature impulse response moments are estimated by a recursive relation involving moments of the input waveform and moments of the observed response. After adapting this method to time domain electromagnetic applications—in particular, MEGATEM and AeroTEM (AirTEM) airborne electromagnetic systems—we present the results from applying this method on synthetic and real data collected over the Reid–Mahaffy test site in northern Ontario, Canada.
Synthesis of Alpha Ferrous Oxalate Dihydrate from Ferrotitaniferous Mineral Sands via Hot Pressurized Aqueous Oxalic Acid: Kinetics and Characterization
Authors: Valdivieso-Ramírez Carla S. , Galeas Salomé , Saldaña Marleny D. A. , Pontón Patricia I. , Guerrero Víctor H. , Vizuete Karla , Debut Alexis , Marinkovic Bojan A.
Published: August 2024

Ferrous oxalate dihydrate is a versatile organic mineral with applications across fields. However, little is known about the feasibility of its synthesis directly from iron-bearing minerals using binary subcritical water (sCW) systems and its associated kinetics. In this study, the sCW+oxalic acid system at either 115 °C or 135 °C was investigated as a reaction medium for ferrous oxalate dihydrate (α-FeC2O4∙2H2O) synthesis, starting from ferrotitaniferous sands. The kinetics of the synthesis reaction were studied, and the physicochemical characterization of the as-synthetized ferrous oxalates was performed. Overall, the sCW synthesis was temperature-dependent, following second-order reaction kinetics according to the proposed precipitation pathway. A high reaction rate constant, significantly high yields (up to 89%), and reduced reaction times (2–8 h) were evident at 135 °C. The as-synthetized product corresponded to the monoclinic α-FeC2O4∙2H2O, showed relatively high specific surface areas (from 31.9 to 33.7 m2∙g−1), and exhibited band gap energies within the visible light range (~2.77 eV). These results suggest that α-FeC2O4∙2H2O can be synthesized using an organic dicarboxylic acid and iron-rich, widely available, low-cost mineral precursors. In addition, the as-prepared α-FeC2O4∙2H2O could be further optimized and tested for catalytic and visible light photocatalytic applications.
A Rock Physics Modeling Method for Metamorphic Rock Reservoirs in Buried Hill
Authors: Hao Hongjian , Zhang Guangzhi , Zhou You
Published: August 2024

The buried hills of the Archean metamorphic rocks in the Bozhong Depression of the Bohai Bay Basin are the main gas-bearing strata, with burial depths ranging from 4000 m to 5500 m. However, metamorphic rocks have internal structural characteristics, such as diverse mineral components, oriented arrangement of mineral particles, complex pore connectivity, variable crystal structures, orthogonal development of multiple sets of fractures, and uneven fluid filling. Compared with conventional reservoirs, they have obvious heterogeneity and anisotropy characteristics. Traditional rock physics modeling methods are no longer suitable for predicting the elastic and anisotropic parameters of metamorphic reservoirs. Therefore, we introduced a vector mixed random medium model to calculate the effect of the oriented arrangement of metamorphic rock minerals on the modulus of the rock matrix and introduced a metamorphic factor to describe the impact of metamorphic recrystallization and alteration metasomatism on the elastic modulus of the rock matrix. Practical applications have shown that the new, improved rock physics modeling method can better estimate the S-wave velocity and anisotropy parameters in wells compared to traditional rock physics modeling methods, providing a reliable basis for predicting fractured reservoirs in metamorphic rock at buried hills.
Diterpenoids with Potent Anti-Psoriasis Activity from Euphorbia helioscopia L.
Authors: Zhao Zhen-Zhu , Liang Xu-Bo , He Hong-Juan , Xue Gui-Min , Sun Yan-Jun , Chen Hui , Zhao Yin-Sheng , Bian Li-Na , Feng Wei-Sheng , Zheng Xiao-Ke
Published: August 2024

Psoriasis, an immune-mediated inflammatory skin disorder, seriously affects the quality of life of nearly four percent of the world population. Euphorbia helioscopia L. is the monarch constituent of Chinese ZeQi powder preparation for psoriasis, so it is necessary to illustrate its active ingredients. Thus, twenty-three diterpenoids, including seven new ones, were isolated from the whole herb of E. helioscopia L. Compounds 1 and 2, each featuring a 2,3-dicarboxylic functionality, are the first examples in the ent-2,3-sceo-atisane or the ent-2,3-sceo-abietane family. Extensive spectroscopic analysis (1D, 2D NMR, and HRMS data) and computational methods were used to confirm their structures and absolute configurations. According to the previous study and NMR data from the jatropha diterpenes obtained in this study, some efficient 1H NMR spectroscopic rules for assigning the relative configurations of 3α-benzyloxy-jatroph-11E-ene and 7,8-seco-3α-benzyloxy-jatropha-11E-ene were summarized. Moreover, the hyperproliferation of T cells and keratinocytes is considered a key pathophysiology of psoriasis. Anti-proliferative activities against induced T/B lymphocytes and HaCaT cells were tested, and IC50 values of some compounds ranged from 6.7 to 31.5 μM. Compounds 7 and 11 reduced the secretions of IFN-γ and IL-2 significantly. Further immunofluorescence experiments and a docking study with NF-κB P65 showed that compound 13 interfered with the proliferation of HaCaT cells by inhibiting the NF-κB P65 phosphorylation at the protein level.
The Development and Application of Tritium-Labeled Compounds in Biomedical Research
Authors: Teng Yu , Yang Hong , Tian Yulin
Published: August 2024

With low background radiation, tritiate compounds exclusively emit intense beta particles without structural changes. This makes them a useful tool in the drug discovery arsenal. Thanks to the recent rapid progress in tritium chemistry, the preparation and analysis of tritium-labeled compounds are now much easier, simpler, and cheaper. Pharmacokinetics, autoradiography, and protein binding studies have been much more efficient with the employment of tritium-labeled compounds. This review provides a comprehensive overview of tritium-labeled compounds regarding their properties, synthesis strategies, and applications.
Insights into the Synergistic Effect and Inhibition Mechanism of Composite Conditioner on Sulfur-Containing Gases during Sewage Sludge Pyrolysis
Authors: Cheng Shan , Chen Lianghui , Wang Shaoshuo , Yao Kehui , Tian Hong
Published: August 2024

Sewage sludge odorous gas release is a key barrier to resource utilization, and conditioners can mitigate the release of sulfur-containing gases. The gas release characteristics and sulfur compound distribution in pyrolysis products under both single and composite conditioning strategies of CaO, Fe2O3, and FeCl3 were investigated. This study focused on the inhibition mechanisms of these conditioners on sulfur-containing gas emissions and compared the theoretical and experimental sulfur content in the products to evaluate the potential synergistic effects of the composite conditioners. The findings indicated that at 650 °C, CaO, Fe2O3, and FeCl3 inhibited H2S release by 35.8%, 23.2%, and 9.1%, respectively. Notably, the composite of CaO with FeCl3 at temperatures ranging from 350 to 450 °C and the combination of Fe2O3 with FeCl3 at 650 °C were found to exert synergistic suppression on H2S emissions. The strongly alkaline CaO inhibited the metathesis reaction between HCl, a decomposition product of FeCl3, and the sulfur-containing compounds within the sewage sludge, thereby exerting a synergistic suppression on the emission of H2S. Conversely, at temperatures exceeding 550 °C, the formation of Ca-Fe compounds, such as FeCa2O4, appeared to diminish the sulfur-fixing capacity of the conditioners, resulting in increased H2S emissions. For instance, the combination of CaO and FeCl3 at 450 °C was found to synergistically reduce H2S emissions by 56.3%, while the combination of CaO and Fe2O3 at 650 °C synergistically enhances the release of H2S by 23.6%. The insights gained from this study are instrumental in optimizing the pyrolysis of sewage sludge, aiming to minimize its environmental footprint and enhance the efficiency of resource recovery.
Quantum Chemical Stability Analysis of Phthalocyanine Metal One-Dimensional Polymers with Bidentate Ligands
Authors: Szwajca Anna , Pankiewicz Radosław
Published: August 2024

The combination of metal–phthalocyanine complexes and axially coordinated organic molecules into polymer chains presents a significant challenge in the synthesis of hybrid materials. A calculated structure for one-dimensional coordinate polymers with N-donor ligands using ab initio (PM6) and DFT (LanL2Dz) methods is presented. DFT methods have shown that there is a linear, one-dimensional structure without distorted geometry for the two bipyridine ligands. The components of the proposed polymers consist of square-planar Zn complexes of phthalocyanine (PcZn) connected via bridging ligands (L). Electronic properties of the monomer PcZnL of zinc phthalocyanine with bidentate ligands have been analyzed using calculations based on density functional theory (B3LYP6-31G(d,p)). Molecular orbital calculations show that this connection between the metallomacrocycle and the conjugated ligand results in a small energy gap, promising molecularly active materials as conductors. The crystallographic reports indicate that obtaining this kind of polymer with the participation of Pc Zn and bidentate ligands is possible.
The Reaction between K2CO3 and Ethylene Glycol in Deep Eutectic Solvents
Authors: Zhou Yi , Chen Mingzhe , Dong Xueling , Yang Dezhong
Published: August 2024

Understanding intermolecular interactions is important for the design of deep eutectic solvents. Herein, potassium carbonate (K2CO3) and ethylene glycol (EG) are used to form deep eutectic solvents. The interactions between K2CO3 and EG are studied using nuclear magnetic resonance (NMR) and Fourier transform infrared (FTIR) spectra. Interestingly, the interaction results indicate that the carbonate anion CO32− can react with EG to form EG-based organic carbonate, which can occur even at room temperature. The possible reaction steps between K2CO3 and EG are presented. As K2CO3 can be prepared from CO2 and KOH, the findings of this work may provide a promising strategy for CO2 capture and conversion.
A Highly Efficient Fluorescent Turn-Off Nanosensor for Quantitative Detection of Teicoplanin Antibiotic from Humans, Food, and Water Based on the Electron Transfer between Imprinted Quantum Dots and the Five-Membered Cyclic Boronate Esters
Authors: Zhang Yansong , Li Daojin , Tian Xiping
Published: August 2024

Teicoplanin has been banned in the veterinary field due to the drug resistance of antibiotics. However, teicoplanin residue from the antibiotic abuse of humans and animals poses a threat to people’s health. Therefore, it is necessary to develop an efficient way for the highly accurate and reliable detection of teicoplanin from humans, food, and water. In this study, novel imprinted quantum dots of teicoplanin were prepared based on boronate affinity-based precisely controlled surface imprinting. The imprinting factor (IF) for teicoplanin was evaluated and reached a high value of 6.51. The results showed excellent sensitivity and selectivity towards teicoplanin. The relative fluorescence intensity was inversely proportional to the concentration of teicoplanin, in the range of 1.0–17 μM. And its limit of detection (LOD) was obtained as 0.714 μM. The fluorescence quenching process was mainly controlled by a static quenching mechanism via the non-radiative electron-transfer process between QDs and the five-membered cyclic boronate esters. The recoveries for the spiked urine, milk, and water samples ranged from 95.33 to 104.17%, 91.83 to 97.33, and 94.22 to 106.67%, respectively.
Synthesis and Properties of α-Phosphate-Modified Nucleoside Triphosphates
Authors: Novgorodtseva Alina I. , Lomzov Alexander A. , Vasilyeva Svetlana V.
Published: August 2024

This review article is focused on the progress made in the synthesis of 5′-α-P-modified nucleoside triphosphates (α-phosphate mimetics). A variety of α-P-modified nucleoside triphosphates (NTPαXYs, Y = O, S; X = S, Se, BH3, alkyl, amine, N-alkyl, imido, or others) have been developed. There is a unique class of nucleoside triphosphate analogs with different properties. The main chemical approaches to the synthesis of NTPαXYs are analyzed and systematized here. Using the data presented here on the diversity of NTPαXYs and their synthesis protocols, it is possible to select an appropriate method for obtaining a desired α-phosphate mimetic. Triphosphates’ substrate properties toward nucleic acid metabolism enzymes are highlighted too. We reviewed some of the most prominent applications of NTPαXYs including the use of modified dNTPs in studies on mechanisms of action of polymerases or in systematic evolution of ligands by exponential enrichment (SELEX). The presence of heteroatoms such as sulfur, selenium, or boron in α-phosphate makes modified triphosphates nuclease resistant. The most distinctive feature of NTPαXYs is that they can be recognized by polymerases. As a result, S-, Se-, or BH3-modified phosphate residues can be incorporated into DNA or RNA. This property has made NTPαXYs a multifunctional tool in molecular biology. This review will be of interest to synthetic chemists, biochemists, biotechnologists, or biologists engaged in basic or applied research.