bluuebunny/crossref_metadata_2025 huggingface dataset:
Theoretical Investigation of Inorganic Particulate Matter: The Case of Water Adsorption on a NaCl Particle Model Studied Using Grand Canonical Monte Carlo Simulations
Authors: Rizza Fabio , Rovaletti Anna , Carbone Giorgio , Miyake Toshiko , Greco Claudio , Cosentino Ugo
Published: October 2023

Sodium chloride (NaCl) represents the principal component of atmospheric particulates of marine origin. To gain a molecular-level understanding of the adsorption process of water vapor on the NaCl surface, Monte Carlo simulations performed in the Grand Canonical ensemble were carried out, considering the water adsorption at different water pressures on a NaCl(001) surface. The calculated adsorption isotherm shows four different regions, whose coverages correspond to those of the low-, transition-, high-, and pre-solution-coverage regions experimentally observed. Detailed analysis reveals how the structure of the adsorbed water molecules (islands, layer, and multi-layer) changes depending on water pressure, and how their orientation with respect to the surface varies with the distance from the surface. This detailed information further supports the picture coming from previous experimental IR absorption spectroscopy studies.
Dynamic Perfusion Computed Tomography for the Assessment of Concomitant Coronary Artery Disease in Patients with a History of Percutaneous Transluminal Angioplasty for Chronic Limb-Threatening Ischemia—A Pilot Study
Authors: Nagy Ferenc T. , Olajos Dorottya , Vattay Borbála , Borzsák Sarolta , Boussoussou Melinda , Deák Mónika , Vecsey-Nagy Milán , Sipos Barbara , Jermendy Ádám L. , Tóth Gábor G. , Nemes Balázs , Merkely Béla , Szili-Török Tamás , Ruzsa Zoltán , Szilveszter Bálint
Published: October 2023

Background: Chronic limb-threatening ischemia (CLTI) is associated with high rates of long-term cardiovascular mortality. Exercise stress testing to detect obstructive coronary artery disease (CAD) can be difficult in this subset of patients due to inability to undergo exercise testing, presence of balanced ischemia and severe coronary artery calcification (CAC). Aim: To test the feasibility of regadenoson stress dynamic perfusion computed tomography (DPCT) in CLTI patients. Methods: Between 2018 and 2023, coronary computed tomography angiography (CTA) and, in the case of a calcium score higher than 400, DPCT, were performed in 25 CLTI patients with a history of endovascular revascularization. Results: Of the 25 patients, 19 had a calcium score higher than 400, requiring DPCT image acquisition. Obstructive CAD could be ruled out in 10 of the 25 patients. Of the 15 CTA/DPCT+ patients, 13 proceeded to coronary angiography (CAG). Revascularization was necessary in all 13 patients. In these 13 patients, vessel-based sensitivity and specificity of coronary CTA/DPCT as compared to invasive evaluation was 75%, respectively. At follow-up (27 ± 21 months) there was no statistically significant difference in all-cause mortality between CTA/DPCT- positive and -negative patients (p = 0.065). Conclusions: Despite a high prevalence of severe CAC, coronary CTA complemented by DPCT may be a feasible method to detect obstructive and functionally significant CAD in CLTI patients.
Retinal Microvasculature Image Analysis Using Optical Coherence Tomography Angiography in Patients with Post-COVID-19 Syndrome
Authors: Noor Maha , McGrath Orlaith , Drira Ines , Aslam Tariq
Published: October 2023

Several optical coherence tomography angiography (OCT-A) studies have demonstrated retinal microvascular changes in patients post-SARS-CoV-2 infection, reflecting retinal-systemic microvasculature homology. Post-COVID-19 syndrome (PCS) entails persistent symptoms following SARS-CoV-2 infection. In this study, we investigated the retinal microvasculature in PCS patients using OCT-angiography and analysed the macular retinal nerve fibre layer (RNFL) and ganglion cell layer (GCL) thickness via spectral domain-OCT (SD-OCT). Conducted at the Manchester Royal Eye Hospital, UK, this cross-sectional study compared 40 PCS participants with 40 healthy controls, who underwent ophthalmic assessments, SD-OCT, and OCT-A imaging. OCT-A images from the superficial capillary plexus (SCP) were analysed using an in-house specialised software, OCT-A vascular image analysis (OCTAVIA), measuring the mean large vessel and capillary intensity, vessel density, ischaemia areas, and foveal avascular zone (FAZ) area and circularity. RNFL and GCL thickness was measured using the OCT machine’s software. Retinal evaluations occurred at an average of 15.2 ± 6.9 months post SARS-CoV-2 infection in PCS participants. Our findings revealed no significant differences between the PCS and control groups in the OCT-A parameters or RNFL and GCL thicknesses, indicating that no long-term damage ensued in the vascular bed or retinal layers within our cohort, providing a degree of reassurance for PCS patients.
Intraoperative Flow Cytometry Upon and Beyond the Cell Cycle: A Case Study of the Characterization of a Bone Metastasis
Authors: Markopoulos Georgios S. , Pakos Emilios E. , Gavrielatos Vasilios , Kosmas Dimitrios , Gkiatas Ioannis , Alexiou George A. , Batistatou Anna , Lampri Evangeli , Vartholomatos George
Published: October 2023

The accurate assessment of malignancy and the precise characterization of cancer type are pivotal in guiding clinical decisions and ensuring optimal patient outcomes. The challenging task of identifying the primary site of carcinoma, especially during a surgical procedure, is not always possible and necessitates the exploration of novel, innovative diagnostic techniques. In this report, we detail a unique case of carcinoma of unknown primary origin encountered during an orthopedic surgical procedure. We introduce a novel intraoperative flow cytometry (iFC) methodology, distinctly different from traditional flow cytometry, which is tailored for real-time assessment during surgeries. This iFC technique, applied in a bone metastasis case of unknown primary origin, enabled DNA content analysis and the quantification of cytokeratin for rapid malignancy characterization, presenting an avenue for immediate surgical guidance and decision making. The case was distinctively characterized using iFC, shedding light on the potential of this emerging technique. iFC has been gaining traction because of its ability to facilitate cancer cell assessment and margin evaluation. It has been successfully applied across a wide spectrum of neoplastic conditions. Our innovative, two-step approach using iFC encompasses (1) DNA content analysis, which serves as a reliable indicator for the detection of cancer cells, and (2) the quantification of cytokeratin, a pivotal marker, which aids in the characterization and classification of a malignancy. In this case, the malignancy was classified as a carcinoma. The findings obtained from iFC were subsequently validated through pathology assessment, confirming the accuracy and reliability of our approach. This noteworthy case strengthens the potential of iFC as a novel tool in malignancy assessment, which is not just limited to cell cycle analysis but instead extends beyond this application. The promising results obtained from this case study serve as a testament to the need for more extensive research in clinical studies.
Simulation of Sea Ice Fragmentation Based on an Improved Voronoi Diagram Algorithm in an Ice Zone Navigation Simulator
Authors: Zhang Boxiang , Ren Hongxiang , Qiu Shaoyang , Yang Xiao , Liao Gongming , Liang Xiao
Published: October 2023

In order to reduce the cost of navigation training in the waters of ice zones and improve the effectiveness of the training process, a method for simulating sea ice fragmentation in an ice zone navigation simulator is proposed. The Voronoi diagram algorithm, which takes the ice thickness into account and affects the degree of fragmentation, was used to preprocess the sea ice model so that the number and sizes of the ice model fragmentations would be related to the ice thickness. According to the position of the preprocessed sub-blocks of the ice model, the collision bodies of the Mesh Collider and Sphere Collider were set up to realize the effect of the conduction of ice cracking as a result of the ship’s hull colliding with the ice surface. Based on the positional relationship between mesh triangle elements and the water surface, the volume of an ice floe that should have been underwater when it reached equilibrium was calculated to achieve the sea-floating effect of the broken ice floe. The quadtree method for the management of sea ice scenes was improved to improve the timeliness of the replacement of the ice model. The experiments show that this method improved the realism of simulations of sea ice breaking in ice zones and can be used for simulations in ice zone navigation simulators.
Flow Characterisation Using Fibre Bragg Gratings and Their Potential Use in Nuclear Thermal Hydraulics Experiments
Authors: Plows Harvey Oliver , Li Jinfeng , Dahlfors Marcus , Margulis Marat
Published: October 2023

With the ever-increasing role that nuclear power is playing to meet the aim of net zero carbon emissions, there is an intensified demand for understanding the thermal hydraulic phenomena at the heart of current and future reactor concepts. In response to this demand, the development of high-resolution flow analysis instrumentation is of increased importance. One such under-utilised and under-researched instrumentation technology, in the context of fluid flow analysis, is fibre Bragg grating (FBG)-based sensors. This technology allows for the construction of simple, minimally invasive instruments that are resistant to high temperatures, high pressures and corrosion, while being adaptable to measure a wide range of fluid properties, including temperature, pressure, refractive index, chemical concentration, flow rate and void fraction—even in opaque media. Furthermore, concertinaing FBG arrays have been developed capable of reconstructing 3D images of large phase structures, such as bubbles in slug flow, that interact with the array. Currently a significantly under-explored application, FBG-based instrumentation thus shows great potential for utilisation in experimental thermal hydraulics; expanding the available flow characterisation and imaging technologies. Therefore, this paper will present an overview of current FBG-based flow characterisation technologies, alongside a systematic review of how these techniques have been utilised in nuclear thermal hydraulics experiments. Finally, a discussion will be presented regarding how these techniques can be further developed and used in nuclear research.
Pseudomonas aeruginosa Strain 91: A Multifaceted Biocontrol Agent against Banana Fusarium Wilt
Authors: Xie Jin , Singh Pratiksha , Qi Yanhua , Singh Rajesh Kumar , Qin Qijian , Jin Cheng , Wang Bin , Fang Wenxia
Published: October 2023

Banana Fusarium wilt (BFW), caused by the soil-borne fungus Fusarium oxysporum f. sp. cubense (Foc), poses significant threats to banana cultivation. Currently, effective control methods are lacking, and biological control has emerged as a possible strategy to manage BFW outbreaks. In this investigation, 109 bacterial strains were isolated from the rhizospheric soil surrounding banana plants in search of potent biological agents against Foc. Strain 91 exhibited the highest antifungal activity against the causal agent of Foc and was identified as Pseudomonas aeruginosa through 16S rRNA gene sequencing and scanning electron microscopy (SEM). Elucidation of strain 91’s inhibitory mechanism against Foc revealed a multifaceted antagonistic approach, encompassing the production of bioactive compounds and the secretion of cell wall hydrolytic enzymes. Furthermore, strain 91 displayed various traits associated with promoting plant growth and showed adaptability to different carbon sources. By genetically tagging with constitutively expressing GFP signals, effective colonization of strain 91 was mainly demonstrated in root followed by leaf and stem tissues. Altogether, our study reveals the potential of P. aeruginosa 91 for biocontrol based on inhibition mechanism, adaptation, and colonization features, thus providing a promising candidate for the control of BFW.
The Effects of Task Repetition Schedules on L2 Fluency Enhancement
Authors: Zhang Meng , Yi Na , Zhou Dandan
Published: October 2023

This article explores the effects of different task repetition schedules on English learners’ oral fluency in terms of speed, breakdown, and repair indices using a PRAAT script to enhance objectivity and consistency in the assessment of learner performances. A total of 90 freshmen participated in the experiment and were divided into three groups: the blocked repetition group, the interleaved repetition group, and a control group. This study adopted a pre- and post-test design. After the learners repetitively practiced the problem-solving tasks for three weeks, their improvement was measured by a new task of the same type. The analyses of speed, breakdown, and repair in learners’ oral performance reported that the experimental groups outperformed the control group in fluency measurement. Specifically, the interleaved repetition group was advantageous compared with the blocked repetition group, except for the silent pause numbers. The findings not only support the interleaving effects and enrich the line of task repetition research but also have pedagogical implications in that introducing interleaved practice in real classrooms is beneficial to L2 speaking enhancement.
‘It’ Is Not for Everyone: Variation in Speakers’ Evaluation of Sociopragmatic Pronouns in Limburgian
Authors: Piepers Joske , Backus Ad , Swanenberg Jos
Published: October 2023

This paper explores the different ways in which speakers of Limburgian think and feel about sociopragmatic pronouns in their dialect, in which women can traditionally be referred to with both ziej ‘she’ and het ‘she’ (lit. ‘it’). Previous research revealed variation between speakers regarding the use of het, which appears to be associated with differences in interpretation and evaluation. This study investigates this further by analyzing how individual speakers evaluate non-feminine pronouns for women. Our data show that many speakers have a relatively high level of awareness, discussing four key themes: (i) how female reference in Limburgian differs from that of Dutch; (ii) the appropriateness of using the pronouns for certain referents and/or in certain social situations; (iii) the various connotations the pronouns may have; and (iv) how they navigate between-speaker differences regarding pronoun evaluation in daily life. Importantly, this high level of awareness is not present in all speakers. These results indicate that the use or non-use of the pronoun het for female referents may be conditioned by cognitive automaticity for some speakers, and by a conscious, emotionally charged consideration about its desirability for others. Our findings, therefore, suggest the importance of integrating cognition and sociality in linguistic theorizing.
Influence of Piston Mass and Working Pressure on the Impact Performance of a Hydraulic Rock Drill Using the Stress Wave Method
Authors: Yang Zhenyi , Li Jun , Yu Guoyan
Published: October 2023

To optimize and improve the impact performance of a hydraulic rock drill, it is helpful to test the stress waves of the drill and analyze the impact energy, impact frequency, and energy utilization rate. For this study, a stress wave test bench was designed and built, according to international standards, in order to study the impact process of a hydraulic rock drill under the working pressures of 18 MPa and 23 MPa. The impact energy, impact frequency, and energy utilization rate of two different hydraulic rock drill pistons in low, middle, and high gear were analyzed using a control variable method. The results demonstrate that the impact stress waves of the rock drill periodically occur in the drill rod, and then decay exponentially until they become close to zero. Moreover, the amplitude of the incident stress wave determines the rock-breaking ability of the drill. The impact energy of the short piston is greater than that of the long piston, with a maximum average value of 346.1 J; the impact frequency of the long piston is higher than that of the short piston, with a maximum average value of 62 Hz; and the energy utilization rate of the short piston is higher than that of the long piston, with a maximum average value of 56.92%, which is close to the theoretical ideal efficiency. Therefore, it can be concluded that the impact performance of a hydraulic rock drill can be effectively tested using the proposed horizontal bench, and that piston characteristics and the working pressure are the main factors affecting impact performance. Accordingly, when developing a hydraulic rock drill, it is advisable to select a shorter piston and a higher working pressure, thus allowing the drill to provide good impact performance.
Observer-Based State Estimation for Recurrent Neural Networks: An Output-Predicting and LPV-Based Approach
Authors: Wang Wanlin , Chen Jinxiong , Huang Zhenkun
Published: October 2023

An innovative cascade predictor is presented in this study to forecast the state of recurrent neural networks (RNNs) with delayed output. This cascade predictor is a chain-structured observer, as opposed to the conventional single observer, and is made up of several sub-observers that individually estimate the state of the neurons at various periods. This new cascade predictor is more useful than the conventional single observer in predicting neural network states when the output delay is arbitrarily large but known. In contrast to examining the stability of error systems solely employing the Lyapunov–Krasovskii functional (LKF), several new global asymptotic stability standards are obtained by combining the application of the Linear Parameter Varying (LPV) approach, LKF and convex principle. Finally, a series of numerical simulations verify the efficacy of the obtained results.
Establishment of Epstein–Barr Virus (EBV) Latent Gene-Expressing T-Cell Lines with an Expression Vector Harboring EBV Nuclear Antigen 1
Authors: Kanno Hiroyuki , Osada Tomohiro , Tateishi Ayako
Published: October 2023

Chronic active Epstein–Barr virus (EBV) infection (CAEBV) is characterized by chronic or recurrent infectious mononucleosis-like symptoms and is associated with EBV-associated T/natural killer (NK)-cell lymphoproliferative disorders, which frequently lead to the development of life-threatening complications, such as virus-associated hemophagocytic syndrome and EBV-positive apparent leukemia/lymphoma mainly in T- and NK-cell lineages. In order to clarify the EBV genes responsible for the diseases, we introduced the plasmid coding sequences of EBV-encoded small RNAs (EBERs) and/or latent membrane protein (LMP) 1 into human T-lymphocyte virus-I-negative human T-cell lines using a gene expression vector harboring EBV nuclear antigen 1, established the G418-resistant transformants of five T-cell lines, and quantitatively examined the expression of EBERs and LMP1 using real-time reverse transcriptase–polymerase chain reaction. The expression levels of EBERs in T-cell transformants with EBER DNA paralleled those in EBV-positive human T- and NK-cell lines, SNTK cells. The expression of LMP1 mRNA varied in SNTK cells and in human T-cell transformants, and the expression of LMP1 mRNA in T-cell lines expressing both EBERs and LMP1 was much lower than that in the same cell line expressing LMP1 mRNA alone. The currently employed gene expression system and currently obtained transformants may be useful for the analyses of the pathophysiology of CAEBV and EBV-positive T/NK-cell lymphoproliferative disorders.
Reduction in Salt Stress Due to the Action of Halophilic Bacteria That Promote Plant Growth in Solanum lycopersicum
Authors: Pérez-Inocencio Javier , Iturriaga Gabriel , Aguirre-Mancilla Cesar L. , Vásquez-Murrieta María Soledad , Lastiri-Hernández Marcos Alfonso , Álvarez-Bernal Dioselina
Published: October 2023

Soil salinity is one of the most important factors reducing agricultural productivity worldwide. Halophilic plant growth-promoting bacteria (H-PGPB) represent an alternative method of alleviating saline stress in crops of agricultural interest. In this study, the following halophilic bacteria were evaluated: Bacillus sp. SVHM1.1, Halomonas sp. SVCN6, Halomonas sp. SVHM8, and a consortium. They were grown under greenhouse conditions in Solanum lycopersicum at different salinity concentrations in irrigation water (0, 20, 60, and 100 mM NaCl) to determine the effects on germination, fruit quality, yield, and concentration of osmoprotectors in plant tissue. Our results demonstrate the influence of halophilic bacteria with the capacity to promote plant growth on the germination and development of Solanum lycopersicum at higher salinity levels. The germination percentage was improved at the highest concentration by the inoculated treatments (from 37 to 47%), as were the length of the radicle (30% at 20 mM) and plumule of the germinated seed, this bacterium also increased the weight of the plumule (97% at 100 mM). They also improved the yield. The dry weight of the plant, in addition to having an influence on the quality of the fruit and the concentration of osmoprotectors (Bacillus sp. SVHM 1.1) had the greatest effect on fruit yield (1.5 kg/plant at 20 mM), by the otherhand, Halomonas sp. SVHM8 provided the best fruit quality characteristics at 100 mM. According to the above results, the efficiency of halophilic PGPB in the attenuation of salt stress in Solanum lycopersicum has been proven.
Integrated Macrogenomics and Metabolomics Explore Alterations and Correlation between Gut Microbiota and Serum Metabolites in Adult Epileptic Patients: A Pilot Study
Authors: Zhou Kaiping , Jia Lijing , Mao Zhuofeng , Si Peipei , Sun Can , Qu Zhenzhen , Wang Weiping
Published: October 2023

Epilepsy (EP) is a complex brain disorder showing a lot of unknows reasons. Recent studies showed that gut microbiota can influence epilepsy via the brain–gut axis. Nevertheless, the mechanism by which gut microbiota affects adult epilepsy still remains unclear. In this study, fecal and serum samples were obtained from patients with epilepsy and normal controls. Using an integrated analysis, sequencing was performed by macrogenomics and high-throughput targeted metabolomics with various bioinformatics approaches. The macrogenomic sequencing revealed significant changes in microbial structure in patients suffering from epilepsy. For example, at the phylum level, the relative abundance of Actinobacteria, Bacteroidetes and Proteobacteria showed an increase in the patients with epilepsy, whereas that of Firmicutes decreased. In addition, the patients with epilepsy had significantly differential metabolite profiles compared to normal controls, and five clusters with 21 metabolites, mainly containing the upregulation of some fatty acids and downregulation of some amino acids. Tryptophan (AUC = 91.81, p < 0.0001), kynurenine (AUC = 79.09, p < 0.01) and 7Z,10Z,13Z,16Z-Docosatetraenoic acid (AUC = 80.95, p < 0.01) may be used as potential diagnostic markers for epilepsy. Differential serum metabolites have effects on tryptophan metabolism, iron death and other pathways. Furthermore, a multiomic joint analysis observed a statistically significant correlation between the differential flora and the differential serum metabolites. In our findings, a macrogenomic analysis revealed the presence of dysregulated intestinal flora species and function in adult epileptic patients. Deeper metabolomic analyses revealed differences in serum metabolites between patients with epilepsy and healthy populations. Meanwhile, the multiomic combination showed connection between the gut microbes and circulating metabolites in the EP patients, which may be potential therapeutic targets.
Autoignition Problem in Homogeneous Combustion Systems: GQL versus QSSA Combined with DRG
Authors: Yu Chunkan , Shashidharan Sudhi , Wu Shuyang , Minuzzi Felipe , Bykov Viatcheslav
Published: October 2023

The global quasi-linearization (GQL) is used as a method to study and to reduce the complexity of mathematical models of mechanisms of chemical kinetics. Similar to standard methodologies, such as the quasi-steady-state assumption (QSSA), the GQL method defines the fast and slow invariant subspaces and uses slow manifolds to gain a reduced representation. It does not require empirical inputs and is based on the eigenvalue and eigenvector decomposition of a linear map approximating the nonlinear vector field of the original system. In the present work, the GQL-based slow/fast decomposition is applied for different combustion systems. The results are compared with the standard QSSA approach. For this, an implicit implementation strategy described by differential algebraic equations (DAEs) systems is suggested and used, which allows for treating both approaches within the same computational framework. Hydrogen–air (with 9 species) and ethanol–air (with 57 species) combustion systems are considered representative examples to illustrate and verify the GQL. The results show that 4D GQL for hydrogen–air and 14D GQL ethanol–air slow manifolds outperform the standard QSSA approach based on a DAE-based reduced computation model.
Sesamin: A Promising Therapeutic Agent for Ameliorating Symptoms of Diabetes
Authors: Huang Shu-Ming , Chuang Cheng-Hung , Rejano Christine Joyce F. , Tayo Lemmuel L. , Hsieh Cheng-Yang , Huang Steven Kuan-Hua , Tsai Po-Wei
Published: October 2023

Diabetes is a chronic metabolic disease characterized by improperly regulating proteins, carbohydrates, and lipids due to insulin deficiency or resistance. The increasing prevalence of diabetes poses a tremendous socioeconomic burden worldwide, resulting in the rise of many studies on Chinese herbal medicines to discover the most effective cure for diabetes. Sesame seeds are among these Chinese herbal medicines that were found to contain various pharmacological activities, including antioxidant and anti-inflammatory properties, lowering cholesterol, improving liver function, blood pressure and sugar lowering, regulating lipid synthesis, and anticancer activities. These medicinal benefits are attributed to sesamin, which is the main lignan found in sesame seeds and oil. In this study, Wistar rat models were induced with type 2 diabetes using streptozotocin (STZ) and nicotinamide, and the effect of sesamin on the changes in body weight, blood sugar level, glycosylated hemoglobin (HbA1c), insulin levels, and the states of the pancreas and liver of the rats were evaluated. The results indicate a reduced blood glucose level, HbA1c, TG, and ALT and AST enzymes after sesamin treatment, while increased insulin level, SOD, CAT, and GPx activities were also observed. These findings prove sesamin’s efficacy in ameliorating the symptoms of diabetes through its potent pharmacological activities.
New Amino Acid-Based Thiosemicarbazones and Hydrazones: Synthesis and Evaluation as Fluorimetric Chemosensors in Aqueous Mixtures
Authors: Esteves Cátia I. C. , Raposo Maria Manuela M. , Costa Susana P. G.
Published: October 2023

Bearing in mind the interest in the development and application of amino acids/peptides as bioinspired systems for sensing, a series of new phenylalanine derivatives bearing thiosemicarbazone and hydrazone units at the side chain were synthesised and evaluated as fluorimetric chemosensors for ions. Thiosemicarbazone and hydrazone moieties were chosen because they are considered both proton-donor and proton-acceptor, which is an interesting feature in the design of chemosensors. The obtained compounds were tested for the recognition of organic and inorganic anions (such as AcO−, F−, Cl−, Br−, I−, ClO4−, CN−, NO3−, BzO−, OH−, H2PO4− and HSO4−) and of alkaline, alkaline-earth, and transition metal cations, (such as Na+, K+, Cs+, Ag+, Cu+, Cu2+, Ca2+, Cd2+, Co2+, Pb2+, Pd2+, Ni2+, Hg2+, Zn2+, Fe2+, Fe3+ and Cr3+) in acetonitrile and its aqueous mixtures in varying ratios via spectrofluorimetric titrations. The results indicate that there is a strong interaction via the donor N, O and S atoms at the side chain of the various phenylalanines, with higher sensitivity for Cu2+, Fe3+ and F− in a 1:2 ligand-ion stoichiometry. The photophysical and metal ion-sensing properties of these phenylalanines suggest that they might be suitable for incorporation into peptide chemosensory frameworks.
Effect of Electron-Beam Irradiation on Functional Compounds and Biological Activities in Peanut Shells
Authors: Han Narae , Lee Jin Young , Kim Mihyang , Kim Jae-Kyung , Lee Yu-Young , Kang Moon Seok , Kim Hyun-Joo
Published: October 2023

Peanut shells, rich in antioxidants, remain underutilized due to limited research. The present study investigated the changes in the functional compound content and skin aging-related enzyme inhibitory activities of peanut shells by electron-beam treatment with different sample states and irradiation doses. In addition, phenolic compounds in the peanut shells were identified and quantified using ultra-performance liquid chromatography with ion mobility mass spectrometry–quadrupole time-of-flight and high-performance liquid chromatography with a photodiode array detector, respectively. Total phenolic compound content in solid treatment gradually increased from 110.31 to 189.03 mg gallic acid equivalent/g as the irradiation dose increased. Additionally, electron-beam irradiation significantly increased 5,7-dihydroxychrome, eriodictyol, and luteolin content in the solid treatment compared to the control. However, liquid treatment was less effective in terms of functional compound content compared to the solid treatment. The enhanced functional compound content in the solid treatment clearly augmented the antioxidant activity of the peanut shells irradiated with an electron-beam. Similarly, electron-beam irradiation substantially increased collagenase and elastase inhibitory activities in the solid treatment. Mutagenicity assay confirmed the stability of toxicity associated with the electron-beam irradiation. In conclusion, electron-beam-irradiated peanut shells could serve as an important by-product with potential applications in functional cosmetic materials.
Statistical Improvement of rGILCC 1 and rPOXA 1B Laccases Activity Assay Conditions Supported by Molecular Dynamics
Authors: Mora-Gamboa María P. C. , Ferrucho-Calle María C. , Ardila-Leal Leidy D. , Rojas-Ojeda Lina M. , Galindo Johan F. , Poutou-Piñales Raúl A. , Pedroza-Rodríguez Aura M. , Quevedo-Hidalgo Balkys E.
Published: October 2023

Laccases (E.C. 1.10.3.2) are glycoproteins widely distributed in nature. Their structural conformation includes three copper sites in their catalytic center, which are responsible for facilitating substrate oxidation, leading to the generation of H2O instead of H2O2. The measurement of laccase activity (UL−1) results may vary depending on the type of laccase, buffer, redox mediators, and substrates employed. The aim was to select the best conditions for rGILCC 1 and rPOXA 1B laccases activity assay. After sequential statistical assays, the molecular dynamics proved to support this process, and we aimed to accumulate valuable insights into the potential application of these enzymes for the degradation of novel substrates with negative environmental implications. Citrate buffer treatment T2 (CB T2) (pH 3.0 ± 0.2; λ420nm, 2 mM ABTS) had the most favorable results, with 7.315 ± 0.131 UL−1 for rGILCC 1 and 5291.665 ± 45.83 UL−1 for rPOXA 1B. The use of citrate buffer increased the enzyme affinity for ABTS since lower Km values occurred for both enzymes (1.49 × 10−2 mM for rGILCC 1 and 3.72 × 10−2 mM for rPOXA 1B) compared to those obtained in acetate buffer (5.36 × 10−2 mM for rGILCC 1 and 1.72 mM for rPOXA 1B). The molecular dynamics of GILCC 1–ABTS and POXA 1B–ABTS showed stable behavior, with root mean square deviation (RMSD) values not exceeding 2.0 Å. Enzyme activities (rGILCC 1 and rPOXA 1B) and 3D model–ABTS interactions (GILCC 1–ABTS and POXA 1B–ABTS) were under the strong influence of pH, wavelength, ions, and ABTS concentration, supported by computational studies identifying the stabilizing residues and interactions. Integration of the experimental and computational approaches yielded a comprehensive understanding of enzyme–substrate interactions, offering potential applications in environmental substrate treatments.
Safety Evaluation of Chlorantraniliprole in Lychee Based on Residue and Dietary Risk Assessment
Authors: Liu Yanping , Wang Xiaonan , Wang Siwei
Published: October 2023

This report presents the development of a highly effective method employing high-performance liquid chromatography–tandem mass spectrometry (HPLC-MS/MS) to investigate chlorantraniliprole’s dissipation, risk assessment, and residue distribution in whole lychee fruit and its pulp. Mean recoveries of the samples ranged from 80 to 105%, exhibiting a relative standard deviation (RSD) of below 8%. The limits of quantification (LOQ) for lychee and pulp were determined as 0.001 mg/kg, and half-lives (t1/2) ranged from 8.0 to 12.2 days. Terminal residue concentrations in whole litchi and pulp were determined as 0.008–0.45 mg/kg and ≤0.001 mg/kg. These residues were treated twice and thrice at two different dosage levels with pre-harvest intervals (PHIs) of 7, 14, and 21 days. The potential chronic risk posed by chlorantraniliprole to humans was non-negligible, as indicated by the risk quotient (RQ) value not exceeding 1. Therefore, this study provides significant fresh data about the safe application of chlorantraniliprole in the production of lychee, which will help China develop maximum residual limits (MRLs).
Advances in Amylases—What’s Going on?
Authors: Janeček Štefan
Published: October 2023

With regard to the CAZy database ( [...]
Critical Pattern Selection Method Based on CNN Embeddings for Full-Chip Optimization
Authors: Zhang Qingyan , Liu Junbo , Zhou Ji , Jin Chuan , Wang Jian , Hu Song , Sun Haifeng
Published: October 2023

Source mask optimization (SMO), a primary resolution enhancement technology, is one of the most pivotal technologies for enhancing lithography imaging quality. Due to the high computation complexity of SMO, patterns should be selected by a selection algorithm before optimization. However, the limitations of existing selection methods are twofold: they are computationally intensive and they produce biased selection results. The representative method having the former limitation is the diffraction signature method. And IBM’s method utilizing the rigid transfer function tends to cause biased selection results. To address this problem, this study proposes a novel pattern cluster and selection algorithm architecture based on a convolutional neural network (CNN). The proposed method provides a paradigm for solving the critical pattern selection problem by CNN to transfer patterns from the source image domain to unified embeddings in a K-dimensional feature space, exhibiting higher efficiency and maintaining high accuracy.
Influence of No-Till System with or without Cover Crops on Stomata Sensitivity of Glyphosate-Tolerant Soybeans to Vapor Pressure Deficit
Authors: Bernier Brillon Jérôme , Moingt Matthieu , Lucotte Marc
Published: October 2023

Soybeans are vulnerable to drought and temperature increases potentially induced by climate change. Hydraulic dysfunction and stomatal closure to avoid excessive transpiration are the main problems caused by drought. The vulnerability of soybeans to drought will depend on the intensity and duration of water stress. The purpose of this study was to determine if the use of cover crops (CCs) can influence the gas exchange potential of glyphosate-tolerant soybeans when the vapor pressure deficit (Vpd) increases. This two-year study was conducted in an open experimental field comprising direct seeding plots with or without CCs. Stomatal conductance (Gs) was measured five times on the same identified leaves following glyphosate-based herbicide application. These leaves were then collected in order to observe the stomata and foliar traits with a scanning electron microscope. The Vpd was calculated concomitantly to Gs measurements at the leaf surface. The results suggest that the use of CCs promotes phenotypic change in soybean leaves (more elaborate venation and a higher abaxial stomatal density), which in turn may enhance their tolerance to drier conditions. In 2019, Gs could be up to 29% higher in plots with CCs compared to those without CCs with similar Vpd values. This study shows that the benefits of using CCs can be observed via the morphological development strategies of the crop plants and their higher tolerance to drought.
Dynamic Optimisation of Fed-Batch Bioreactors for mAbs: Sensitivity Analysis of Feed Nutrient Manipulation Profiles
Authors: Jones Wil , Gerogiorgis Dimitrios
Published: October 2023

Successful cultivation of mammalian cells must consider careful formulation of culture media consisting of a variety of substrates and amino acids. A widely cited method for quantifying metabolic networks of mammalian cultures is dynamic flux balance modelling. Application of in-silico techniques allows researchers to circumvent time-consuming and costly in-vivo experimentation. Dynamic simulation and optimisation of reliable models allows for the visualization of opportunities to improve throughputs of target protein products, such as monoclonal antibodies (mAbs). This study presents a sensitivity analysis comparing dynamic optimisation results for industrial-scale fed-batch bioreactors, considering a variety of initial conditions. Optimized feeding trajectories are computed via Nonlinear Programming (NLP) model, employing the established IPOPT solver. Glucose, then glutamine, then asparagine, can lead to improved mAb yields and viable cell counts.
Mindfulness in Catholic Primary Schools: An Irish Perspective
Authors: Carroll Thomas
Published: October 2023

Irish Catholic primary education operates within a context increasingly marked by detraditionalisation and secularisation. As religious belief and identity recedes in Ireland, Catholic schools face challenges in enabling the children they serve to develop a personal relationship with God and nurturing their faith formation and development, an important element of the mission of the Catholic school. At the same time, mindfulness practice has grown exponentially in popularity across many sectors of society, including in Irish education. A growing body of research supports mindfulness practice in schools, citing benefits such as improved academic performance and enhanced wellbeing. This review examines the development of mindfulness practice in Irish Catholic primary schools. Curricular reform in primary education regarding the growing role of wellbeing is explored. The review also addresses opportunities and challenges to mindfulness practice in these schools.
Remote Sensing of Climate-Vegetation Dynamics and Their Effects on Ecosystems
Authors: Chang Chung-Te , Chiang Jyh-Min , Dai Junhu
Published: October 2023

Vegetation phenology, i [...]
Data-Driven Approaches for Wildfire Mapping and Prediction Assessment Using a Convolutional Neural Network (CNN)
Authors: Kanwal Rida , Rafaqat Warda , Iqbal Mansoor , Weiguo Song
Published: October 2023

As wildfires become increasingly perilous amidst Pakistan’s expanding population and evolving environmental conditions, their global significance necessitates urgent attention and concerted efforts toward proactive measures and international cooperation. This research strives to comprehensively enhance wildfire prediction and management by implementing various measures to contribute to proactive mitigation in Pakistan. Additionally, the objective of this research was to acquire an extensive understanding of the factors that influence fire patterns in the country. For this purpose, we looked at the spatiotemporal patterns and causes of wildfires between 2000 and 2023 using descriptive analysis. The data analysis included a discussion on density-based clustering as well as the distribution of the data across four seasons over a period of six years. Factors that could indicate the probability of a fire occurrence such as weather conditions, terrain characteristics, and fuel availability encompass details about the soil, economy, and vegetation. We used a convolutional neural network (CNN) to extract features, and different machine learning (ML) techniques were implemented to obtain the best model for wildfire prediction. The majority of fires in the past six years have primarily occurred during the winter months in coastal locations. The occurrence of fires was accurately predicted by ML models such as random forest (RF), which outperformed competing models. Meanwhile, a CNN with 1D and 2D was used for more improvement in prediction by ML models. The accuracy increased from an 86.48 to 91.34 accuracy score by just using a CNN 1D. For more feature extraction, a CNN 2D was used on the same dataset, which led to state-of-the-art prediction results. A 96.91 accuracy score was achieved by further tuning the RF model on the total data. Data division by spatial and temporal changes was also used for the better prediction of fire, which can further be helpful for understanding the different prospects of wildfire. This research aims to advance wildfire prediction methodologies by leveraging ML techniques to explore the benefits and limitations of capturing complex patterns and relationships in large datasets. Policymakers, environmentalists, and scholars studying climate change can benefit greatly from the study’s analytical approach, which may assist Pakistan in better managing and reducing wildfires.
Deformation Monitoring and Dynamic Analysis of Long-Runout Bedding Landslide Based on InSAR and Particle Flow Code
Authors: Gao Yang , Li Jun , Liu Xiaojie , Wu Weile , Zhang Han , Liu Pengfei
Published: October 2023

Long-runout landslides occur frequently in the sandstone and mudstone mountainous areas in southwestern China under heavy rainfall conditions. This has been a key issue in the field of disaster prevention and reduction. Considering the Niuerwan landslide in Wulong, Chongqing, on 13 July 2020, as an example, we employed technical methodologies, including unmanned aerial vehicle (UAV) images, field investigation, geological condition analysis (including geomorphology and topography, stratigraphic structure and formation lithology, etc.), interferometric synthetic aperture radar (InSAR) monitoring and Particle Flow Code 3D (PFC3D) simulations to study failure mechanism and a long-runout motion model of flow-like landslides induced by the heavy rainfall. The results showed that (1) the large differences between the upper and lower strata are the root cause of the instability and long-runout fluidization movement; (2) heavy rainfall is the key driving factor of slope instability and deep-seated landslides, leading to long-distance movement of the upper saturated residual soil; (3) the long-runout fluidization model of bedding landslides is mainly divided into the overall sliding in the lower layer, the mixing of coarse and fine particles in the middle layer, and saturation fluidization in the upper layer; and (4) the long-runout fluidization process of bedding landslides is composed of three stages: overall instability, mixed acceleration, and fluidization accumulation. In view of these findings, in the risk evaluation and prediction of long-runout fluidization landslides in sandstone and mudstone mountainous areas, this particular disaster model can be used to provide quantitative references for disaster prevention and mitigation.
Role of Temperature-Dependent Interfacial Tension on Shear Wave Velocity for Energy Geosystems
Authors: Park Junghee , Kim Jongchan
Published: October 2023

Interfacial tension varies with temperature. This paper investigates the effects of temperature-dependent interfacial tension on shear wave velocity. We designed a nylon cell equipped with bender elements in a cross-hole configuration to measure the shear wave velocity of nine sand–silt mixtures with different degrees of saturation (S = 0%, 2.5%, 5%, 10%, and 100%). All specimens were subjected to a temperature change from 10 °C to 1 °C. The results demonstrate that shear wave velocity tends to be very sensitive to changes in temperature at a low degree of saturation. Particle-scale analyses overlapped with the experimental results and captured the critical role of temperature-dependent interfacial tension in small-strain skeletal stiffness. In fact, the temperature should be considered during laboratory and field shear modulus measurements of the long-term performance of energy geosystems subjected to thermally induced repetitive loads.
6G-Powered Efficient Resource Control through IRS-UE Association
Authors: Alqahtani Ali , Taneja Ashu , Alqahtani Jarallah , Alqahtani Nayef
Published: October 2023

The widespread popularity of live streaming, cloud gaming, mobile video streaming, and many real-time applications relies on high-speed data to ensure low latency and seamless user experience. This large high-speed data demand has led to the development of next-generation or sixth-generation (6G) communication technology. It aims to offer high-speed communication support to multiple applications and interactive services simultaneously. But the vulnerability of node communication to the changing propagation environment often leads to call drops, data loss, and high latency. This paper presents a 6G-enabled wireless network that makes use of multiple intelligent reflecting surfaces (IRSs). The distributed IRSs enhance the robustness of transmission but the increased overhead owing to multiple IRSs is the main challenge. To overcome this, efficient resource control is introduced, which associates sets of IRSs to user equipment (UE). An algorithm, namely IUABP (IRS-UE association based on pilots), is proposed; it offers selective resource control. Furthermore, the performance of the distributed IRS system is evaluated based on the achievable sum rate for different IRS numbers, reflecting elements, and transmit powers. We observed that the proposed association scheme offers an improvement of 30% in the achieved sum rate using N = 50 and R = 5 at a transmit power of 12 dBm. We also discuss the comparison with two other association schemes, namely, distance-based association and random association.
Metabolic Stability of Eight Airborne OrganoPhosphate Flame Retardants (OPFRs) in Human Liver, Skin Microsomes and Human Hepatocytes
Authors: Di Bona Stefano , Artino Emanuele , Buiarelli Francesca , Di Filippo Patrizia , Galarini Roberta , Lorenzetti Stefano , Lucarelli Franco , Cruciani Gabriele , Goracci Laura
Published: October 2023

The waste of electrical and electronic equipment (WEEE) is generally considered a secondary raw material for the recovery of valuable components. However, emerging issues regarding the impact of suspended particles arising from WEEE recycling operations are a concern. It was recently demonstrated that samples from three different WEEE plants were rich in organophosphate flame retardants (OPFRs). Since exposure to a xenobiotic can lead to its biotransformation through human metabolism routes, in the present study, the metabolism of eight OPFRs of interest in our sampling campaign (triphenyl phosphate (TPhP), tri-m-tolyl phosphate (TMTP), ethylhexyl diphenyl phosphate (EHDPhP), tributoxyethyl phosphate (TBOEP), diphenyl phosphate (DPhP), trichloroethyl phosphate (TCEP), tris(1,3-dichloropropan-2-yl) phosphate (TDClPP) and bisphenol A bis(diphenyl phosphate) (BDP)) was investigated. Their metabolism was studied at different time points in three matrices: human liver microsomes, human hepatocytes and human skin microsomes. This study, which was run using a common experimental setting, allowed easy comparison of results for each OPFR of interest, and a comparison with other data in the literature was performed. In particular, a number of metabolites not previously described were detected, and for the first time, it was shown that TPhP could be metabolized in human skin microsomes.