bluuebunny/crossref_metadata_2025 huggingface dataset:
How Doping Regulates As(III) Adsorption at TiO2 Surfaces: A DFT + U Study
Authors: Huang Xiaoxiao , Wu Mengru , Huang Rongying , Yang Gang
Published: August 2024

The efficient adsorption and removal of As(III), which is highly toxic, remains difficult. TiO2 shows promise in this field, though the process needs improvement. Herein, how doping regulates As(OH)3 adsorption over TiO2 surfaces is comprehensively investigated by means of the DFT + D3 approach. Doping creates the bidentate mononuclear (Ce doping at the Ti5c site), tridentate (N, S doping at the O2c site), and other new adsorption structures. The extent of structural perturbation correlates with the atomic radius when doping the Ti site (Ce >> Fe, Mn, V >> B), while it correlates with the likelihood of forming more bonds when doping the O site (N > S > F). Doping the O2c, O3c rather than the Ti5c site is more effective in enhancing As(OH)3 adsorption and also causes more structural perturbation and diversity. Similar to the scenario of pristine surfaces, the bidentate binuclear complexes with two Ti-OAs bonds are often the most preferred, except for B doping at the Ti5c site, S doping at the O2c site, and B doping at the O3c site of rutile (110) and Ce, B doping at the Ti5c site, N, S doping at the O2c site, and N, S, B doping at the O3c site of anatase (101). Doping significantly regulates the As(OH)3 adsorption efficacy, and the adsorption energies reach −4.17, −4.13, and −4.67 eV for Mn doping at the Ti5c site and N doping at the O2c and O3c sites of rutile (110) and −1.99, −2.29, and −2.24 eV for Ce doping at the Ti5c site and N doping at the O2c and O3c sites of anatase (101), respectively. As(OH)3 adsorption and removal are crystal-dependent and become apparently more efficient for rutile vs. anatase, whether doped at the Ti5c, O2c, or O3c site. The auto-oxidation of As(III) occurs when the As centers interact directly with the TiO2 surface, and this occurs more frequently for rutile rather than anatase. The multidentate adsorption of As(OH)3 causes electron back-donation and As(V) re-reduction to As(IV). The regulatory effects of doping during As(III) adsorption and the critical roles played by crystal control are further unraveled at the molecular level. Significant insights are provided for As(III) pollution management via the adsorption and rational design of efficient scavengers.
A Combined Computational and Experimental Approach to Studying Tropomyosin Kinase Receptor B Binders for Potential Treatment of Neurodegenerative Diseases
Authors: Nguyen Duc D. , Mansur Shomit , Ciesla Lukasz , Gray Nora E. , Zhao Shan , Bao Yuping
Published: August 2024

Tropomyosin kinase receptor B (TrkB) has been explored as a therapeutic target for neurological and psychiatric disorders. However, the development of TrkB agonists was hindered by our poor understanding of the TrkB agonist binding location and affinity (both affect the regulation of disorder types). This motivated us to develop a combined computational and experimental approach to study TrkB binders. First, we developed a docking method to simulate the binding affinity of TrkB and binders identified by our magnetic drug screening platform from Gotu kola extracts. The Fred Docking scores from the docking computation showed strong agreement with the experimental results. Subsequently, using this screening platform, we identified a list of compounds from the NIH clinical collection library and applied the same docking studies. From the Fred Docking scores, we selected two compounds for TrkB activation tests. Interestingly, the ability of the compounds to increase dendritic arborization in hippocampal neurons matched well with the computational results. Finally, we performed a detailed binding analysis of the top candidates and compared them with the best-characterized TrkB agonist, 7,8-dyhydroxyflavon. The screening platform directly identifies TrkB binders, and the computational approach allows for the quick selection of top candidates with potential biological activities based on the docking scores.
Solid-State Construction of CuO–Cu2O@C with Synergistic Effects of Pseudocapacity and Carbon Coating for Enhanced Electrochemical Lithium Storage
Authors: Du Guifen , Gong Piyu , Cui Chuansheng , Wang Lei , An Changhua
Published: August 2024

The pseudocapacitive effect can improve the electrochemical lithium storage capacity at high-rate current density. However, the cycle stability is still unsatisfactory. To overcome this issue, a multivalent oxide with a carbon coating represents a plausible technique. In this work, a CuO–Cu2O@C composite has been constructed by a one-step bilayer salt-baking process and utilized as anode material for lithium-ion batteries. At a current density of 2.0 A g−1, the as-prepared composite delivered a stable discharge capacity of 431.8 mA h g−1 even after 600 cycles. The synergistic effects of the multivalence, the pseudocapacitive contribution from copper, and the carbon coating contribute to the enhanced electrochemical lithium storage performance. Specifically, the existence of cuprous suboxide improves the electrochemical conductivity, the pseudocapacitive effect enhances the lithium storage capacity, and the presence of carbon ensures cycle stability. The testing results show that CuO–Cu2O@C composite has broad application prospects in portable energy storage devices. The present work provides an instructive precedent for the preparation of transition metal oxides with controllable electronic states and excellent electrochemical performance.
Novel ST1926 Nanoparticle Drug Formulation Enhances Drug Therapeutic Efficiency in Colorectal Cancer Xenografted Mice
Authors: Assi Sara , Hayar Berthe , Pisano Claudio , Darwiche Nadine , Saad Walid
Published: August 2024

Cancer is a major public health problem that ranks as the second leading cause of death. Anti-cancer drug development presents with various hurdles faced throughout the process. Nanoparticle (NP) formulations have emerged as a promising strategy for enhancing drug delivery efficiency, improving stability, and reducing drug toxicity. Previous studies have shown that the adamantyl retinoid ST1926 displays potent anti-tumor activities in several types of tumors, particularly in colorectal cancer (CRC). However, phase I clinical trials in cancer patients using ST1926 are halted due to its low bioavailability. In this manuscript, we developed ST1926-NPs using flash nanoprecipitation with polystyrene-b-poly (ethyleneoxide) as an amphiphilic stabilizer and cholesterol as a co-stabilizer. Dynamic light scattering revealed that the resulting ST1926-NPs Contin diameter was 97 nm, with a polydispersity index of 0.206. Using cell viability, cell cycle analysis, and cell death assays, we showed that ST1926-NP exhibited potent anti-tumor activities in human CRC HCT116 cells. In a CRC xenograft model, mice treated with ST1926-NP exhibited significantly lowered tumor volumes compared to controls at low drug concentrations and enhanced the delivery of ST1926 to the tumors. These findings highlight the potential of ST1926-NPs in attenuating CRC tumor growth, facilitating its further development in clinical settings.
Prospecting of the Antioxidant Activity from Extracts Obtained from Chañar (Geoffroea decorticans) Seeds Evaluated In Vitro and In Vivo Using the Tenebrio molitor Model
Authors: Silva Ariana Pereira , Cordeiro Maria Lucia da Silva , Aquino-Martins Verônica Giuliani de Queiroz , de Moura Melo Luciana Fentanes , Paiva Weslley de Souza , Naliato Georggia Fatima da Silva , Theodoro Raquel Cordeiro , Meneses Carlos Henrique Salvino Gadelha , Rocha Hugo Alexandre Oliveira , Scortecci Katia Castanho
Published: August 2024

Geoffroea decorticans, commonly known as Chañar, is a native Chilean plant widely used in folk medicine for its expectorant, pain relief, and antinociceptive properties. This study explored the antioxidant, cytotoxic, and protective effects of its ethanolic (EE) and aqueous (EA) seed extracts against oxidative stress induced by copper sulfate, using both in vitro and in vivo approaches. Phytochemical analyses revealed the presence of phenolic compounds and flavonoids in the extracts. High-Performance Liquid Chromatography (HPLC) coupled with Gas Chromatography-Mass Spectrometry/Mass Spectrometry (GC-MS/MS) identified significant components such as phytol, alpha-tocopherol, vitexin, and rutin, with the EE being particularly rich in phytol and vitexin. Antioxidant assays—measuring the total antioxidant capacity (TAC), reducing power, DPPH radical scavenging, and copper and iron chelation—confirmed their potent antioxidant capabilities. Both extracts were non-cytotoxic and provided protection against CuSO4-induced oxidative stress in the 3T3 cell line. Additionally, the use of Tenebrio molitor as an invertebrate model underscored the extracts’ antioxidant and protective potentials, especially that of the EE. In conclusion, this study highlights the significant antioxidant and protective properties of Chañar seed extracts, particularly the ethanolic extract, in both in vitro and in vivo models.
Current Evidence on Nutrient Intakes and Infant Growth: A Narrative Review of Baby-Led Weaning vs. Conventional Weaning
Authors: Matzeller Kinzie L. , Krebs Nancy F. , Tang Minghua
Published: August 2024

Throughout infancy, changes in growth and development are observed, including changes in nutritional requirements; at approximately 6 months of age, when complementary feeding begins, breastmilk and/or formula are no longer the sole source of energy and nutrients. Little is known about the impact of complementary feeding (CF) approaches used during this time on infant nutrition and growth. Baby-led weaning (BLW) has continued to gain popularity over the last two decades, emphasizing the importance of examining the adequacy of different CF methods. This narrative review of 19 studies from January 2010 to April 2024 aims to discuss the differences between BLW and conventional weaning (CW). The definition of BLW varied across studies, and no standard definition has been established. Though no differences in energy were reported, macronutrient and micronutrient intakes were variable between approaches, including for micronutrients such as iron and zinc. Of the few studies with growth data, results comparing BLW and CW were conflicting. Differences were seen in the demographics of parents who chose to follow BLW and breastfeeding prevalence and duration prior to complementary feeding. Additional research is needed to understand the impacts of BLW and CW on nutrient intakes and growth to inform recommendations for infant complementary feeding approaches.
Approachable Synthetic Methodologies for Second-Generation β-Lactamase Inhibitors: A Review
Authors: Fatima Noor , Khalid Shehla , Rasool Nasir , Imran Muhammad , Parveen Bushra , Kanwal Aqsa , Irimie Marius , Ciurea Codrut Ioan
Published: August 2024

Some antibiotics that are frequently employed are β-lactams. In light of the hydrolytic process of β-lactamase, found in Gram-negative bacteria, inhibitors of β-lactamase (BLIs) have been produced. Examples of first-generation β-lactamase inhibitors include sulbactam, clavulanic acid, and tazobactam. Many kinds of bacteria immune to inhibitors have appeared, and none cover all the β-lactamase classes. Various methods have been utilized to develop second-generation β-lactamase inhibitors possessing new structures and facilitate the formation of diazabicyclooctane (DBO), cyclic boronate, metallo-, and dual-nature β-lactamase inhibitors. This review describes numerous promising second-generation β-lactamase inhibitors, including vaborbactam, avibactam, and cyclic boronate serine-β-lactamase inhibitors. Furthermore, it covers developments and methods for synthesizing MβL (metallo-β-lactamase inhibitors), which are clinically effective, as well as the various dual-nature-based inhibitors of β-lactamases that have been developed. Several combinations are still only used in preclinical or clinical research, although only a few are currently used in clinics. This review comprises materials on the research progress of BLIs over the last five years. It highlights the ongoing need to produce new and unique BLIs to counter the appearance of multidrug-resistant bacteria. At present, second-generation BLIs represent an efficient and successful strategy.
Etravirine Prevents West Nile Virus and Chikungunya Virus Infection Both In Vitro and In Vivo by Inhibiting Viral Replication
Authors: Zheng Xu , He Yanhua , Xia Binghui , Tang Wanda , Zhang Congcong , Wang Dawei , Tang Hailin , Zhao Ping , Peng Haoran , Liu Yangang
Published: August 2024

Diseases transmitted by arthropod-borne viruses such as West Nile virus (WNV) and chikungunya virus (CHIKV) pose threat to global public health. Unfortunately, to date, there is no available approved drug for severe symptoms caused by both viruses. It has been reported that reverse transcriptase inhibitors can effectively inhibit RNA polymerase activity of RNA viruses. We screened the anti-WNV activity of the FDA-approved reverse transcriptase inhibitor library and found that 4 out of 27 compounds showed significant antiviral activity. Among the candidates, etravirine markedly inhibited WNV infection in both Huh 7 and SH-SY5Y cells. Further assays revealed that etravirine inhibited the infection of multiple arboviruses, including yellow fever virus (YFV), tick-borne encephalitis virus (TBEV), and CHIKV. A deeper study at the phase of action showed that the drug works primarily during the viral replication process. This was supported by the strong interaction potential between etravirine and the RNA-dependent RNA polymerase (RdRp) of WNV and alphaviruses, as evaluated using molecular docking. In vivo, etravirine significantly rescued mice from WNV infection-induced weight loss, severe neurological symptoms, and death, as well as reduced the viral load and inflammatory cytokines in target tissues. Etravirine showed antiviral effects in both arthrophlogosis and lethal mouse models of CHIKV infection. This study revealed that etravirine is an effective anti-WNV and CHIKV arbovirus agent both in vitro and in vivo due to the inhibition of viral replication, providing promising candidates for clinical application.
Adipose-Derived Stem-Cell-Membrane-Coated PLGA-PEI Nanoparticles Promote Wound Healing via Efficient Delivery of miR-21
Authors: Peng Huiyu , Du Fangzhou , Wang Jingwen , Wu Yue , Wei Qian , Chen Aoying , Duan Yuhan , Shi Shuaiguang , Zhang Jingzhong , Yu Shuang
Published: August 2024

miRNAs have been shown to be involved in the regulation of a variety of physiological and pathological processes, but their use in the treatment of diseases is still limited due to their instability. Biomimetic nanomaterials combine nanomaterials with cellular components that are readily modifiable and biocompatible, making them an emerging miRNA delivery vehicle. In this study, adipose-derived MSC membranes were wrapped around PLGA-PEI loaded with miR-21 through co-extrusion and later transplanted into C57BL/6 mice wounds. The wound-healing rate, epithelialization, angiogenesis, and collagen deposition were assessed after treatment and corroborated in vitro. Our study demonstrated that m/NP/miR-21 can promote wound healing in terms of epithelialization, dermal reconstruction, and neovascularization, and it can regulate the corresponding functions of keratinocytes, fibroblasts, and vascular endothelial cells. m/NP/miR-21 can inhibit the expression of PTEN, a gene downstream of miR-21, and increase the phosphorylation activation of AKT, which can then regulate the functions of fibroblasts. In conclusion, this provides a new approach to therapy for skin wounds using microRNA transporters and biomimetic nanoparticles.
The “Leafing Intensity Premium” Hypothesis and the Scaling Relationships of the Functional Traits of Bamboo Species
Authors: Yao Weihao , Shi Peijian , Wang Jinfeng , Mu Youying , Cao Jiajie , Niklas Karl J.
Published: August 2024

The “leafing intensity premium” hypothesis proposes that leaf size results from natural selection acting on different leafing intensities, i.e., the number of leaves per unit shoot volume or mass. The scaling relationships among various above-ground functional traits in the context of this hypothesis are important for understanding plant growth and ecology. Yet, they have not been sufficiently studied. In this study, we selected four bamboo species of the genus Indocalamus Nakai and measured the total leaf fresh mass per culm, total non-leaf above-ground fresh mass, total number of leaves per culm, and above-ground culm height of 90 culms from each species. These data were used to calculate leafing intensity (i.e., the total number of leaves per culm divided by the total non-leaf above-ground fresh mass) and mean leaf fresh mass per culm (i.e., the total leaf fresh mass per culm divided by the total number of leaves per culm). Reduced major axis regression protocols were then used to determine the scaling relationships among the various above-ground functional traits and leafing intensity. Among the four species, three exhibited an isometric (one-to-one) relationship between the total leaf fresh mass per culm and the total non-leaf above-ground fresh mass, whereas one species (Indocalamus pumilus) exhibited an allometric (not one-to-one) relationship. A negative isometric relationship was found between the mean leaf fresh mass per culm and the leafing intensity for one species (Indocalamus pedalis), whereas three negative allometric relationships between mean leaf fresh mass per culm and leafing intensity were observed for the other three species and the pooled data. An exploration of the alternative definitions of “leafing intensity” showed that the total number of leaves per culm divided by the above-ground culm height is superior because it facilitates the non-destructive calculation of leafing intensity for Indocalamus species. These results not only confirm the leafing intensity premium hypothesis for bamboo species but also highlight the interconnected scaling relationships among different functional traits, thereby contributing to our understanding of the ecological and evolutionary significance of leaf size variation and biomass investment strategies.
Elevated CO2 and Nitrogen Supply Boost N Use Efficiency and Wheat (T. aestivum cv. Yunmai) Growth and Differentiate Soil Microbial Communities Related to Ammonia Oxidization
Authors: Dong Xingshui , Lin Hui , Wang Feng , Shi Songmei , Sharifi Sharifullah , Wang Shuai , Ma Junwei , He Xinhua
Published: August 2024

Elevated CO2 levels (eCO2) pose challenges to wheat (Triticum aestivum L.) growth, potentially leading to a decline in quality and productivity. This study addresses the effects of two ambient CO2 concentrations (aCO2, daytime/nighttime = 410/450 ± 30 ppm and eCO2, 550/600 ± 30 ppm) and two nitrogen (N) supplements (without N supply—N0 and with 100 mg N supply as urea per kg soil—N100) on wheat (T. aestivum cv. Yunmai) growth, N accumulation, and soil microbial communities related to ammonia oxidization. The data showed that the N supply effectively mitigated the negative impacts of eCO2 on wheat growth by reducing intercellular CO2 concentrations while enhancing photosynthesis parameters. Notably, the N supply significantly increased N concentrations in wheat tissues and biomass production, thereby boosting N accumulation in seeds, shoots, and roots. eCO2 increased the agronomic efficiency of applied N (AEN) and the physiological efficiency of applied N (PEN) under N supply. Plant tissue N concentrations and accumulations are positively related to plant biomass production and soil NO3−-N. Additionally, the N supply increased the richness and evenness of the soil microbial community, particularly Nitrososphaeraceae, Nitrosospira, and Nitrosomonas, which responded differently to N availability under both aCO2 and eCO2. These results underscore the importance and complexity of optimizing N supply and eCO2 for enhancing crop tissue N accumulation and yield production as well as activating nitrification-related microbial activities for soil inorganic N availability under future global environment change scenarios.
Possible Mechanism of Sucrose and Trehalose-6-Phosphate in Regulating the Secondary Flower on the Strong Upright Spring Shoots of Blueberry Planted in Greenhouse
Authors: Wu Hui-Ling , Zhang Sui-Lin , Feng Xin , Zhang Ya-Qian , Zhou Bing-Jie , Cao Man , Wang Ya-Ping , Guo Bao-Shi , Hou Zhi-Xia
Published: August 2024

Secondary flowering is the phenomenon in which a tree blooms twice or more times a year. Along with the development of blueberry (Vaccinium corymbosum L.) fruits in spring, a large number of secondary flowers on the strong upright spring shoots were noticed in blueberries planted in the greenhouse. To reveal the cause and possible regulatory mechanism of the phenomenon, we clarified the phenological characteristics of flower bud differentiation and development on the spring shoots by combining phenological phenotype with anatomical observation. Furthermore, the changes in carbohydrates, trehalose-6-phosphate (Tre6P), and the relationship among the key enzyme regulatory genes for Tre6P metabolism and the key regulatory genes for flower formation during the differentiation process of apical buds and axillary buds were investigated. The results showed that the process of flower bud differentiation and flowering of apical and axillary buds was consistent, accompanied by a large amount of carbohydrate consumption. This process was positively correlated with the expression trends of VcTPS1/2, VcSnRK1, VcFT, VcLFY2, VcSPL43, VcAP1, and VcDAM in general, and negatively correlated with that of VcTPP. In addition, there is a certain difference in the differentiation progress of flower buds between the apical and axillary buds. Compared with axillary buds, apical buds had higher contents of sucrose, fructose, glucose, Tre6P, and higher expression levels of VcTPS2, VcFT, VcSPL43, and VcAP1. Moreover, VcTPS1 and VcTPS2 were more closely related to the physiological substances (sucrose and Tre6P) in axillary bud and apical bud differentiation, respectively. It was suggested that sucrose and trehalose-6-phosphate play a crucial role in promoting flower bud differentiation in strong upright spring shoots, and VcTPS1 and VcTPS2 might play a central role in these activities. Our study provided substantial sight for further study on the mechanism of multiple flowering of blueberries and laid a foundation for the regulation and utilization of the phenomenon of multiple flowering in a growing season of perennial woody plants.
Machine Learning-Based Tomato Fruit Shape Classification System
Authors: Vazquez Dana V. , Spetale Flavio E. , Nankar Amol N. , Grozeva Stanislava , Rodríguez  Gustavo R.
Published: August 2024

Fruit shape significantly impacts the quality and commercial value of tomatoes (Solanum lycopersicum L.). Precise grading is essential to elucidate the genetic basis of fruit shape in breeding programs, cultivar descriptions, and variety registration. Despite this, fruit shape classification is still primarily based on subjective visual inspection, leading to time-consuming and labor-intensive processes prone to human error. This study presents a novel approach incorporating machine learning techniques to establish a robust fruit shape classification system. We trained and evaluated seven supervised machine learning algorithms by leveraging a public dataset derived from the Tomato Analyzer tool and considering the current four classification systems as label variables. Subsequently, based on class-specific metrics, we derived a novel classification framework comprising seven discernible shape classes. The results demonstrate the superiority of the Support Vector Machine model in terms of its accuracy, surpassing human classifiers across all classification systems. The new classification system achieved the highest accuracy, averaging 88%, and maintained a similar performance when validated with an independent dataset. Positioned as a common standard, this system contributes to standardizing tomato fruit shape classification, enhancing accuracy, and promoting consensus among researchers. Its implementation will serve as a valuable tool for overcoming bias in visual classification, thereby fostering a deeper understanding of consumer preferences and facilitating genetic studies on fruit shape morphometry.
Hydrogen-Rich Syngas Production from Waste Textile Gasification Coupling with Catalytic Reforming under Steam Atmosphere
Authors: Zhuang Xinchao , Zhu Nengwu , Li Fei , Lin Haisheng , Liang Chao , Dang Zhi , Zou Yuquan
Published: August 2024

The average annual global production of waste textiles exceeds 92 million tons, with the majority landfilled and incinerated, resulting in energy waste and environmental pollution. In this study, a thermal conversion process for waste textiles by gasification coupling with catalytic reforming under a steam atmosphere was proposed. The gasification performance of the waste textiles jumped with the introduction of steam and catalyst compared to pyrolysis at 800 °C. The syngas yield increased from 20.86 to 80.97 mmol/g and the hydrogen concentration increased from 17.79 to 50.91 vol.%, which was an increase of 288.12% and 186.18%, respectively. The excellent gasification performance mainly came from two sources: steam promotion for volatiles production and Fe-N-BC promotion for steam reforming of volatiles by Fe2O3, Fe3O4, Fe-Nx, etc. This study has achieved the efficient production of hydrogen-rich syngas from waste textiles, providing a new idea and theoretical basis for the effective removal and utilization of waste textiles.
Bio-Recovery of Metals through Biomining within Circularity-Based Solutions
Authors: Cozma Petronela , Bețianu Camelia , Hlihor Raluca-Maria , Simion Isabela Maria , Gavrilescu Maria
Published: August 2024

Given the current highest demand in history for raw materials, there is a growing demand for the recovery of key metals from secondary sources, in order to prevent metal depletion and to reduce the risk of toxic discharges into the environment. This paper focuses on the current nature-based solutions (i.e., biomining and bioleaching) applied to resource recovery (metals) from solid matrices. Biomining exploits the potential of microorganisms to facilitate the extraction and recovery of metals from a wide range of waste materials as an interesting alternative, replacing primary raw materials with secondary material resources (thus improving metal recycling rates in the context of the circular economy). Special attention was paid to the analysis of metal biomining from a process sustainability perspective. In this regard, several supporting tools (e.g., life cycle assessment, LCA), developed to assist decision-makers in the complex process of assessing and scaling-up remediation projects (including biomining), were discussed. The application of LCA in biomining is still evolving, and requires comprehensive case studies to improve the methodological approach. This review outlines the fact that few studies have focused on demonstrating the environmental performance of the biomining process. Also, further studies should be performed to promote the commercial opportunities of biomining, which can be used to recover and recycle metals from solid matrices and for site remediation. Despite some important disadvantages (poor process kinetics; metal toxicity), biomining is considered to be a cleaner approach than conventional mining processes. However, implementing it on a large scale requires improvements in regulatory issues and public acceptance.
Mimicking Marine Conditions to Improve Prodigiosin Yields in Bioreactor
Authors: Pereira Ricardo F. S. , de Carvalho Carla C. C. R.
Published: August 2024

Prodigiosin is a red bacterial pigment with great potential as a natural dye and drug precursor, while presenting several pharmacological properties, including antimicrobial and anticancer activities. Its commercialization for biomedical applications, however, remains scarce. The major limitations are related to the lack of efficient bioprocesses and scaling up from laboratory to production. In the present work, the upstream process for prodigiosin production was developed using a marine Serratia rubidaea isolated from a sample collected near a shallow-water hydrothermal vent. The yield of product per biomass was found to be influenced by the cell concentration in the inoculum. The system was scaled up to 2 L stirred tank reactors with two different vessel geometries. It was shown that the vessel geometry and a cascade control mode for regulating the dissolved oxygen concentration influenced the volumetric oxygen mass transfer coefficient (kLa) and thus prodigiosin production. To improve product yields, strategies to mimic the aeration conditions found at the sampling site were tested. When the inoculum was grown for 5 h at 200 rpm and for 19 h at 25 rpm, which significantly decreased the oxygen available, the cells produced 588.2 mgproduct/gbiomass, corresponding to a production of 1066.2 mg of prodigiosin in 24 h and a productivity of 36.1 mgproduct/(L.h). This is a 3.7-fold increase in prodigiosin yield and a 4.5-fold increase in productivity in relation to when no particular strategy was promoted. Additionally, it was shown that lipid analysis and flow cytometry may be used as reliable at-line analytical tools, allowing the monitoring of cell condition and prodigiosin production during fermentation.
Religious Education in Australia: The Voices of Practitioners and Scholars
Authors: Hall David , Sultmann William Francis , Lamb Janeen Therese
Published: August 2024

Religious education (RE) in Australia is challenged to support the religious and spiritual needs of Australia’s religiously plural student population. Within a national colloquium, practitioners and scholars (N = 57) gathered to discern ways forward in RE. Data were collected from small and whole group discussions reported across three days of integrated reflection on themes of Awaken, Celebrate, and Imagine. Interpretative phenomenological analysis (IPA) and Leximancer were used to analyse the respective data which confirmed domains of focus on Day 1 of Formation, Curriculum, Pedagogy, Partnerships, and Research. Day 2 (Celebrate) explored these domains and identified Themes and Theoretical Propositions that advanced each domain. Day 3 (Imagine) underlined foundations in faith for each domain and detailed generic propositions and themes. Propositions included advancing RE through Formation (being attentive to personal readiness, curriculum intention, and school identity), Pedagogy (engaging practices of inquiry, experiential learning, and encounter-based opportunities), Curriculum (characterised as inclusive, relevant, and life-giving), Partnerships (strengthening inclusion and engagement with family, parish, and community), and Research (integrating evidence-based practice).
Science and Philosophy in a Thomistic Anthropology of Sexual Difference
Authors: Finley John DeSilva
Published: August 2024

This essay examines the relation between scientific inquiry and philosophical thought in the context of a Thomistic account of human sexual difference. I begin by considering Thomas’s own view and its explicit though brief appeal to biological observation. In particular, I focus on his claim that being male or female stems more from a substance’s matter than from its form. Then, I look at a fairly recent exchange between William Newton and myself, in which, drawing upon Thomistic thought in the context of contemporary science, we argued opposing positions. Mine held that sex stems more from form than from matter, while Newton maintained that Thomas’s original position is better. In reviewing this exchange, I note strengths in Newton’s argument and suggest a further distinction, even while concluding that my fundamental position is still a better account. Lastly, I turn to further questions and the necessity of continued partnership between philosophy and science.
Causes of Increased Compound Temperature and Precipitation Extreme Events in the Arid Region of Northwest China from 1961 to 2100
Authors: Niu Huihui , Sun Weijun , Huai Baojuan , Wang Yuzhe , Chen Rensheng , Han Chuntan , Wang Yingshan , Zhou Jiaying , Wang Lei
Published: August 2024

Compound extreme events pose more grave threats to human health, the natural environment, and socioeconomic systems than do individual extreme events. However, the drivers and spatiotemporal change characteristics of compound extreme events under climate transition remain poorly understood, especially in the arid region of Northwest China. This study examined the spatiotemporal change characteristics and driving mechanisms of extreme temperature and precipitation compound events in Northwest China based on data from 86 national meteorological stations and 11 climate models of the Coupled Model Intercomparison Project, Phase 6. The results indicated that (1) the frequency values of heat extremity–dry (1.60/10a) and heat extremity–heavy precipitation (0.60/10a) events increased from 1961 to 2020, and showed a faster uptrend after 1990 than before. (2) Under four shared socioeconomic pathway scenarios, there is also the likelihood of an upward trend in heat extremity–dry and heat extremity–heavy precipitation events in Northwest China by the end of 21 century, especially under SSP585, with probability values of 1.70/10a and 1.00/10a, respectively. (3) A soil moisture deficit leads to decreased evaporation and increased sensible heat by reduction in the soil–atmosphere exchange; the non-adiabatic heating process leads to a higher frequency of hot days. This land–air interaction feedback mechanism is a significant driver of heat extremity–dry events in Northwest China. (4) In the Northwest China region, the warmer trend surpasses the wetter trend, contributing to increased specific humidity, and the vapor pressure deficit may lead to an increasing frequency of extreme precipitation, consequently increasing heat extremity–heavy precipitation events. These results provide new insights for the understanding of compound extreme events, in order to cope with their risks.
Multi-Stage Feature Fusion of Multispectral and SAR Satellite Images for Seasonal Crop-Type Mapping at Regional Scale Using an Adapted 3D U-Net Model
Authors: Wittstruck Lucas , Jarmer Thomas , Waske Björn
Published: August 2024

Earth observation missions such as Sentinel and Landsat support the large-scale identification of agricultural crops by providing free radar and multispectral satellite images. The extraction of representative image information as well as the combination of different image sources for improved feature selection still represent a major challenge in the field of remote sensing. In this paper, we propose a novel three-dimensional (3D) deep learning U-Net model to fuse multi-level image features from multispectral and synthetic aperture radar (SAR) time series data for seasonal crop-type mapping at a regional scale. For this purpose, we used a dual-stream U-Net with a 3D squeeze-and-excitation fusion module applied at multiple stages in the network to progressively extract and combine multispectral and SAR image features. Additionally, we introduced a distinctive method for generating patch-based multitemporal multispectral composites by selective image sampling within a 14-day window, prioritizing those with minimal cloud cover. The classification results showed that the proposed network provided the best overall accuracy (94.5%) compared to conventional two-dimensional (2D) and three-dimensional U-Net models (2D: 92.6% and 3D: 94.2%). Our network successfully learned multi-modal dependencies between the multispectral and SAR satellite images, leading to improved field mapping of spectrally similar and heterogeneous classes while mitigating the limitations imposed by persistent cloud coverage. Additionally, the feature representations extracted by the proposed network demonstrated their transferability to a new cropping season, providing a reliable mapping of spatio-temporal crop type patterns.
An Unsupervised Learning Tool for Plaque Tissue Characterization in Histopathological Images
Authors: Fraschini Matteo , Castagnola Massimo , Barberini Luigi , Sanfilippo Roberto , Coghe Ferdinando , Didaci Luca , Cau Riccardo , Frongia Claudio , Scartozzi Mario , Saba Luca , Faa Gavino
Published: August 2024

Stroke is the second leading cause of death and a major cause of disability around the world, and the development of atherosclerotic plaques in the carotid arteries is generally considered the leading cause of severe cerebrovascular events. In recent years, new reports have reinforced the role of an accurate histopathological analysis of carotid plaques to perform the stratification of affected patients and proceed to the correct prevention of complications. This work proposes applying an unsupervised learning approach to analyze complex whole-slide images (WSIs) of atherosclerotic carotid plaques to allow a simple and fast examination of their most relevant features. All the code developed for the present analysis is freely available. The proposed method offers qualitative and quantitative tools to assist pathologists in examining the complexity of whole-slide images of carotid atherosclerotic plaques more effectively. Nevertheless, future studies using supervised methods should provide evidence of the correspondence between the clusters estimated using the proposed textural-based approach and the regions manually annotated by expert pathologists.
An Evaluation of Multi-Channel Sensors and Density Estimation Learning for Detecting Fire Blight Disease in Pear Orchards
Authors: Veres Matthew , Tarry Cole , Grigg-McGuffin Kristy , McFadden-Smith Wendy , Moussa Medhat
Published: August 2024

Fire blight is an infectious disease found in apple and pear orchards. While managing the disease is critical to maintaining orchard health, identifying symptoms early is a challenging task which requires trained expert personnel. This paper presents an inspection technique that targets individual symptoms via deep learning and density estimation. We evaluate the effects of including multi-spectral sensors in the model’s pipeline. Results show that adding near infrared (NIR) channels can help improve prediction performance and that density estimation can detect possible symptoms when severity is in the mid-high range.
Non-Intrusive System for Honeybee Recognition Based on Audio Signals and Maximum Likelihood Classification by Autoencoder
Authors: Libal Urszula , Biernacki Pawel
Published: August 2024

Artificial intelligence and Internet of Things are playing an increasingly important role in monitoring beehives. In this paper, we propose a method for automatic recognition of honeybee type by analyzing the sound generated by worker bees and drone bees during their flight close to an entrance to a beehive. We conducted a wide comparative study to determine the most effective preprocessing of audio signals for the detection problem. We compared the results for several different methods for signal representation in the frequency domain, including mel-frequency cepstral coefficients (MFCCs), gammatone cepstral coefficients (GTCCs), the multiple signal classification method (MUSIC) and parametric estimation of power spectral density (PSD) by the Burg algorithm. The coefficients serve as inputs for an autoencoder neural network to discriminate drone bees from worker bees. The classification is based on the reconstruction error of the signal representations produced by the autoencoder. We propose a novel approach to class separation by the autoencoder neural network with various thresholds between decision areas, including the maximum likelihood threshold for the reconstruction error. By classifying real-life signals, we demonstrated that it is possible to differentiate drone bees and worker bees based solely on audio signals. The attained level of detection accuracy enables the creation of an efficient automatic system for beekeepers.
Vibration Characteristics of Magnetostrictive Composite Cantilever Resonator with Nonlocal Effect
Authors: Xu Yan , Shang Xinchun , Xu Ke
Published: August 2024

Taking the nonlocal effect into account, the vibration governing differential equation and boundary conditions of a magnetostrictive composite cantilever resonator were established based on the Euler magnetoelastic beam theory. The frequency equation and vibration mode function of the composite cantilever were obtained by means of the separation of variables method and the analytic solution of ordinary differential equations. The lateral deflection, vibration governing equations, and boundary conditions were nondimensionalized. Furthermore, the natural frequency and modal function of the composite beam were quantitatively analyzed with different nonlocal parameters and transverse geometry dimensions using numerical examples. Compared with the results without considering the nonlocal effect, the influence of the nonlocal effect on the vibration characteristics was analyzed. The numerical results show that the frequency shift and frequency band narrowing of the magnetostrictive cantilever resonator are induced by nonlocal effects. In particular, the high-frequency vibration characteristics, such as vibration amplitude and modal node of the composite beam, are significantly affected. These analysis results can provide a reference for the functional design and optimization of magnetostrictive resonators.
Dense Convolutional Neural Network-Based Deep Learning Pipeline for Pre-Identification of Circular Leaf Spot Disease of Diospyros kaki Leaves Using Optical Coherence Tomography
Authors: Kalupahana Deshan , Kahatapitiya Nipun Shantha , Silva Bhagya Nathali , Kim Jeehyun , Jeon Mansik , Wijenayake Udaya , Wijesinghe Ruchire Eranga
Published: August 2024

Circular leaf spot (CLS) disease poses a significant threat to persimmon cultivation, leading to substantial harvest reductions. Existing visual and destructive inspection methods suffer from subjectivity, limited accuracy, and considerable time consumption. This study presents an automated pre-identification method of the disease through a deep learning (DL) based pipeline integrated with optical coherence tomography (OCT), thereby addressing the highlighted issues with the existing methods. The investigation yielded promising outcomes by employing transfer learning with pre-trained DL models, specifically DenseNet-121 and VGG-16. The DenseNet-121 model excels in differentiating among three stages of CLS disease (healthy (H), apparently healthy (or healthy-infected (HI)), and infected (I)). The model achieved precision values of 0.7823 for class-H, 0.9005 for class-HI, and 0.7027 for class-I, supported by recall values of 0.8953 for class-HI and 0.8387 for class-I. Moreover, the performance of CLS detection was enhanced by a supplemental quality inspection model utilizing VGG-16, which attained an accuracy of 98.99% in discriminating between low-detail and high-detail images. Moreover, this study employed a combination of LAMP and A-scan for the dataset labeling process, significantly enhancing the accuracy of the models. Overall, this study underscores the potential of DL techniques integrated with OCT to enhance disease identification processes in agricultural settings, particularly in persimmon cultivation, by offering efficient and objective pre-identification of CLS and enabling early intervention and management strategies.
EmotionCast: An Emotion-Driven Intelligent Broadcasting System for Dynamic Camera Switching
Authors: Zhang Xinyi , Ba Xinran , Hu Feng , Yuan Jin
Published: August 2024

Traditional broadcasting methods often result in fatigue and decision-making errors when dealing with complex and diverse live content. Current research on intelligent broadcasting primarily relies on preset rules and model-based decisions, which have limited capabilities for understanding emotional dynamics. To address these issues, this study proposed and developed an emotion-driven intelligent broadcasting system, EmotionCast, to enhance the efficiency of camera switching during live broadcasts through decisions based on multimodal emotion recognition technology. Initially, the system employs sensing technologies to collect real-time video and audio data from multiple cameras, utilizing deep learning algorithms to analyze facial expressions and vocal tone cues for emotion detection. Subsequently, the visual, audio, and textual analyses were integrated to generate an emotional score for each camera. Finally, the score for each camera shot at the current time point was calculated by combining the current emotion score with the optimal scores from the preceding time window. This approach ensured optimal camera switching, thereby enabling swift responses to emotional changes. EmotionCast can be applied in various sensing environments such as sports events, concerts, and large-scale performances. The experimental results demonstrate that EmotionCast excels in switching accuracy, emotional resonance, and audience satisfaction, significantly enhancing emotional engagement compared to traditional broadcasting methods.
Bedside Magnetocardiography with a Scalar Sensor Array
Authors: Iwata Geoffrey Z. , Nguyen Christian T. , Tharratt Kevin , Ruf Maximilian , Reinhardt Tucker , Crivelli-Decker Jordan , Liddy Madelaine S. Z. , Rugar Alison E. , Lu Frances , Aschbacher Kirstin , Pratt Ethan J. , Au-Yeung Kit Yee , Bogdanovic Stefan
Published: August 2024

Decades of research have shown that magnetocardiography (MCG) has the potential to improve cardiac care decisions. However, sensor and system limitations have prevented its widespread adoption in clinical practice. We report an MCG system built around an array of scalar, optically pumped magnetometers (OPMs) that effectively rejects ambient magnetic interference without magnetic shielding. We successfully used this system, in conjunction with custom hardware and noise rejection algorithms, to record magneto-cardiograms and functional magnetic field maps from 30 volunteers in a regular downtown office environment. This demonstrates the technical feasibility of deploying our device architecture at the point-of-care, a key step in making MCG usable in real-world settings.
Combined Impact of Heart Rate Sensor Placements with Respiratory Rate and Minute Ventilation on Oxygen Uptake Prediction
Authors: Lu Zhihui , Yang Junchao , Tao Kuan , Li Xiangxin , Xu Haoqi , Qiu Junqiang
Published: August 2024

Oxygen uptake (V˙O2) is an essential metric for evaluating cardiopulmonary health and athletic performance, which can barely be directly measured. Heart rate (HR) is a prominent physiological indicator correlated with V˙O2 and is often used for indirect V˙O2 prediction. This study investigates the impact of HR placement on V˙O2 prediction accuracy by analyzing HR data combined with the respiratory rate (RESP) and minute ventilation (V˙E) from three anatomical locations: the chest; arm; and wrist. Twenty-eight healthy adults participated in incremental and constant workload cycling tests at various intensities. Data on V˙O2, RESP, V˙E, and HR were collected and used to develop a neural network model for V˙O2 prediction. The influence of HR position on prediction accuracy was assessed via Bland–Altman plots, and model performance was evaluated by mean absolute error (MAE), coefficient of determination (R2), and mean absolute percentage error (MAPE). Our findings indicate that HR combined with RESP and V˙E (V˙O2HR+RESP+V˙E) produces the most accurate V˙O2 predictions (MAE: 165 mL/min, R2: 0.87, MAPE: 15.91%). Notably, as exercise intensity increases, the accuracy of V˙O2 prediction decreases, particularly within high-intensity exercise. The substitution of HR with different anatomical sites significantly impacts V˙O2 prediction accuracy, with wrist placement showing a more profound effect compared to arm placement. In conclusion, this study underscores the importance of considering HR placement in V˙O2 prediction models, with RESP and V˙E serving as effective compensatory factors. These findings contribute to refining indirect V˙O2 estimation methods, enhancing their predictive capabilities across different exercise intensities and anatomical placements.