bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mesoporous SiO2-chitin/MoO3 Nanocomposite: Synthesis, Surface Investigation, Uptake Potential for Pb(II) and Cu(II), and Future Outlook
Authors: Heiba Hany Fathy , Taha Asia A. , Mostafa Alaa R. , Elsaharty Abeer , Mahmoud Manal G. , Mohamed Laila A. 
Published: September 2024

Abstract

A highly mesoporous SiO2-chitin supported MoO3 nanocomposite was synthesized and characterized for immobilizing Pb(II) and Cu(II) from water. This composite combines MoO3 for interactions, chitin for chelation, and silica for stability. XPS and FTIR and zeta potential investigations showed alterations in binding energies, metal-oxygen coordination bonds and surface charge highlighting an interplay in the removal mechanism between electrostatic attraction and surface complexation. The composite's features include a high surface area (266.95 m2/g), pore volume (0.48 cm3/g), and well-defined mesoporous structure (mean pore diameter: 7.192 nm). S-TEM confirmed uniform distribution of Si, O, and Mo with localized Mo concentration. XRD confirmed well-crystallized MoO3 nanoparticles in an amorphous SiO2-chitin matrix. Metal removal was affected by pH, time, concentration, and dose. Kinetics followed a pseudo-second-order model, with intraparticle diffusion and multilayer heterogeneous adsorption per Freundlich isotherm. Langmuir capacities were 16.05 mg/g for Cu(II) and 27.30 mg/g for Pb(II). Thermodynamic data suggested endothermic, spontaneous adsorption with stronger Pb(II) affinity. Activation energy values (Cu(II): 15.36 kJ/mol, Pb(II): 20.48 kJ/mol) supported chemisorption as the primary mechanism. The study highlights the nanocomposite's potential for Cu(II) and Pb(II) removal.
Phytochemical compositions and Adulticidal Effectiveness of Indian Borage, Coleus amboinicus Lour, against Maize Weevil, Sitophilus zeamais Motschulsky [Coleoptera: Curculionidae]
Authors: Ashamo Michael Olufemi , Ileke Kayode David , Yesufu Opeyemi Sarah 
Published: September 2024

Abstract

The use of synthetic chemical insecticides in the management of food grains pest have a serious adverse effect on consumer’s health and the environment. Public awareness of the adverse effects of the synthetic chemical insecticides has called for the urgent need to replace this method with safer and cheap method. This research evaluated the adulticidal effects of Coleus amboinicus leaf, stem and root powders and crude extracts against Sitophilus zeamais. The plant powders were tested at dosage 0.1, 0.3, 0.6, 0.9 and 1.5 g per 20 grams, while extracts were tested at concentration 0.1, 0.2, 0.3, 0.4 and 0.5 ml per 20 grams of maize seeds. The results revealed that Coleus amboinicus leaf powder at dosage 1.5g caused 63% mortality of adult S. zeamais after a day of treatment. This followed by C. amboinicus stem that evoked 56% weevil mortality. This research showed that C. amboinicus extracts were more toxic than powders of the tested Coleus amboinicus parts. The lethal concentration of leaf, stem and root extracts which caused 50% mortality in the population of S. zeamais response after 96 hours of exposure were 0.13 ml, 0.27ml and 0.48ml respectively. Coleus amboinicus leaf proved to be the most toxic to maize weevil, followed by stem powder and extract. The study established C. amboinicus leaf, stem, and root contain varying levels of phytochemicals, such as alkaloids, saponin, flavonoids, and tannin, which are responsible for the adulticidal toxicity to the maize weevil.
Graph convolutional network for predicting abnormal grain growth in Monte Carlo simulations of microstructural evolution
Authors: Holm Elizabeth , Cohn Ryan 
Published: September 2024

Abstract

Recent developments in graph neural networks show promise for predicting the occurrence of abnormal grain growth, which has been a particularly challenging area of research due to its apparent stochastic nature. In this study, we generate a large dataset of Monte Carlo simulations of abnormal grain growth. We train simple graph convolution networks to predict which initial microstructures will exhibit abnormal grain growth, and compare the results to a standard computer vision approach for the same task. The graph neural network outperformed the computer vision method and achieved 73% prediction accuracy and fewer false positives. It also provided some physical insight into feature importance and the relevant length scale required to maximize predictive performance. Analysis of the uncertainty in the Monte Carlo simulations provides additional insights for ongoing work in this area.
A power analysis framework to aid the design of robust semi-field vector control experiments
Authors: Kipingu Andrea M. , Lwatoejera Dickson W. , Ng’habi Kija R. , Kiware Samson S. , Viana Mafalda , Johnson Paul C. D. 
Published: September 2024

Abstract

Background Semi-field experiments are an efficient way of assessing the impacts of potential new vector control tools (VCTs) before field trials. However, their design is critically important to ensure their results are unbiased and informative. An essential element of the design of semi-field experiments is power analysis, which empowers researchers to ensure that only designs with adequate statistical power are adopted. In this study, a methodology was developed, and its use was demonstrated in a tutorial, to determine the required number of semi-field chambers, sampling frequency and the number of mosquitoes required to achieve sufficient power for evaluating the impact of a single VCT or two in combination.Methods By analysing data simulated from a generalized linear mixed-effects model, power was estimated for various experimental designs, including short- (24 hours) vs. long-term (3 months) experiments and single vs. combined application of interventions (e.g., insecticide-treated nets combined with pyriproxyfen autodissemination).Results Although power increased with increasing number of chambers, sampling frequency and the number of mosquitoes, the number of chambers and variance between chambers were the dominant factors determining power relative to all other design choices. High variance between chambers decreased power, highlighting the importance of making conditions similar among chambers, by reducing variation if possible and by rotating variables if not. As compared to a single intervention, an additional intervention required an increase in the number of chambers, while short and long experiments were similar in terms of key aspects such as the number of chambers per treatment.Conclusion Determining the most efficient experimental design for a semi-field experiment will depend on a balance of design choices and resource constraints. The power analysis framework and tutorial provided here can aid in the robust design of these widely used experiments and ultimately facilitate the development of new vector control tools (VTCs).
Topical delivery of human single-domain antibody targeting IL-33 for inhibiting mucosal inflammation
Authors: Ying Tianlei , Huang Keke , Wu Yuqing , Kong Yu , Xu Qingyuan , Zhang Yirou , Li Quanxiao , Li Cheng , Song Wenping , Zhu Xiaoyi , Yang Zhenlin , Xin Changchang , Zhou Xujiao , Wu Yanling , Hong Jiaxu 
Published: September 2024

Abstract

Addressing mucosal inflammatory disorders in the ocular surface or respiratory system remains a formidable challenge due to limited penetration of biological therapeutics across epithelial barriers. In this study, we explored the potential of human single-domain antibodies (UdAbs) as topical therapeutics for the targeted modulation of interleukin-33 (IL-33) in two mucosal-associated inflammatory disorders. The anti-IL-33 UdAb, designated A12, demonstrated potent inhibition of the IL-33-mediated signaling pathway, despite not blocking IL-33 receptor interaction. The topical delivery of A12 achieved significantly elevated corneal concentrations in vivo compared to anti-IL-33 control IgG Itepekimab, which exhibited negligible ocular penetration. Meanwhile, A12 ameliorated the dry eye disease severity considerably by exerting anti-inflammatory effects. Furthermore, in another murine model of allergic asthma, inhaled A12 substantially reduced overall lung inflammation. Our findings revealed the capacity of UdAbs to penetrate mucosal barriers following non-invasive localized delivery, highlighting their potential as an innovative therapeutic strategy for modulating mucosal inflammation.
Holocene paleoenvironmental reconstruction based on the lacustrine evolution of three Cameroonian lakes (SW, Africa)
Authors: Bessa Armel Zacharie Ekoa , Kołaczek Piotr , Ndjigui Paul-Désiré , Adatte Thierry , Bomou Brahimsamba , Armstrong-Altrin John S. 
Published: September 2024

Abstract

Lakes are the most attractive and expressive characteristics of a landscape. Lacustrine sediments provide a historical record of the conditions of the surrounding catchment area. The aim of this study is to reconstruct the Holocene lacustrine evolution of 3 lakes located in Yaoundé, Dizangué and Ngaoundéré regions (Cameroon, SW-Africa) using a multiproxy approach including analysis of sediments, diatoms, pollen, with absolute chronologies based on radiocarbon dates. Sediment cores were recovered from a raft using polyvinyl chloride (PVC) pipe. Sediment grains are generally sub-rounded and rounded indicative of both aeolian and fluvial transportation. Pollen and diatom data revealed major hydrological changes and strong fluctuations between wet conditions during the "Medieval Warm Period" (1100 − 800 yrs BP), and dry conditions during the "Little Ice Age" (500 − 300 yrs BP). Four distinct paleoclimatic phases were identified from the diatom assemblage of lakes from Yaoundé and Dizangué (South) and Ngaoundéré (North). The diatom assemblages in Simbock Lake (southern Cameroon) indicate high water levels initially, followed by a transition marked by increased aerophilic species, potentially indicating episodic drying or reduced water supply. Furthermore, a pH and trophic inversion suggests eutrophication due to nutrient influx. In the Ossa Lake complex (southern Cameroon), four phases reveal changes from oligotrophic to eutrophic conditions, with Aulacoseira species dominating, and the evolution of acidic to clear waters. Lake Ngaoundaba in the Adamawa (northern Cameroon) exhibits three phases, indicating stable oligotrophic conditions, episodic drying, and a rise in lake level with increased tychoplanktonic species, particularly Aulacoseira distans. These hydrological changes have controlled the dynamics of tropical rainforests during the Little Ice Age (LIA) and the Medieval Warming (MW) in this part of Africa, resulting in their expansion during periods of heavy rainfall and contraction during periods of reduced rainfall.
Bayesian Geo-Additive Model to Analyze Spatial Pattern and Determinants of Maternal Mortality in Ethiopia
Authors: Eshetu Yitagesu , Getachew Tigist 
Published: September 2024

Abstract

Background and Aims: Maternal mortality is defined as the death of a woman from any cause associated to or made worse by her pregnancy, either during her pregnancy or within 42 days of the pregnancy's termination, regardless of the length of the pregnancy or its location. The objective of this study is to determine the factors influencing maternal mortality as well as to examine the regional distribution of maternal deaths in Ethiopia.
Method:This study was conducted in Ethiopia and the data was basically secondary which is
obtained from 2016 Ethiopian Demographic and Health survey (EDHS). The Bayesian Geo-additive regression model is used to identify the major risk factors and spatial effects (spatial
pattern) on maternal death in Ethiopia.
Result:Pregnancy-related problems or childbirth were the cause of death for 1.43% of the 10,009 women in the research, whose ages ranged from 15 to 49. In contrast to the semi-parametric and generalized linear models, the Bayesian Geo-additive regression model is based on the DIC and better fits the data. According to the Bayesian Geo-additive regression model's results, maternal death is significantly affected by the place of delivery, the number of prenatal care visits, marital status, wealth index, mother's age and the number of birth orders. The Afar, Somali, Benishangul Gumuz, and Gambela regions have higher rates of maternal death, according to evidence of geographic variation in a model.
Conclusion:The findings of the study revealed that maternal mortality is influenced by numerous social, demographic, and geographic variables. Geographic variations exist in the patterns of maternal mortality.
Local-structure insight into the improved superconducting properties of Pb-substituted La(O,F)BiS2: A photoelectron holography study
Authors: Li YaJun , Hashimoto Yusuke , Kataoka Noriyuki , Sun ZeXu , Kawamura Sota , Tomita Hiroto , Setoguchi Taro , Takeuchi Soichiro , Koga Shunjo , Yamagami Kohei , Kotani Yoshinori , Demura Satoshi , Noguchi Kanako , Sakata Hideaki , Matsushita Tomohiro , Wakita Takanori , Muraoka Yuji , Yokoya Takayoshi 
Published: September 2024

Abstract

Pb-substituted La(O,F)BiS2 (Pb-LaOFBiS2) exhibits improved superconducting properties and a resistivity anomaly around 100 K that is attributed to a structural transition. We have performed temperature(T)-dependent photoelectron holography (PEH) to study dopant incorporation sites and the local structure change across the anomaly. PEH study of Pb-LaOFBiS2 provided evidence for the dominant incorporation sites of Pb and F: Pb atoms are incorporated into the Bi sites and F atoms are incorporated into the O site. No remarkable difference in the local structures around Pb and Bi atoms were observed. Across the temperature of the resistivity anomaly (T*), photoelectron holograms of Bi 4f changed. Comparison of holograms with those of non-substituted LaOFBiS2 sample, as well as simulated holograms, suggested that (1), above T*, the tetragonal structure of Pb-LaOFBiS2 are different from the tetragonal structure of LaOFBiS2 and (2), below T*, the tetragonal structure still remains in Pb-LaOFBiS2. We discuss possible origin of the difference in the structure above T* and implication of the result below T*, which are necessary ingredients to understand the physical properties of Pb-LaOFBiS2.
Novel syntheses of wide-band gap semiconducting Cdx Znx-1 Co2O4 of spinel nanostructure: Characterization and optical properties
Authors: Abd-Elrahman M. I. , Rashad Latifa , Mohamed H. A. , Taya Y. A. , El-Fadl A. Abu 
Published: September 2024

Abstract

Cadmium doped zinc cobaltite spinel structure in the form of CdxZnx-1Co2O4 (0 ≤ x ≤ 1) are synthesized by sol-gel method. A good crystallinity of the ZnCo2O4 and its dopants samples are indicated by the sharpness and strong peaks of X-ray diffraction patterns. The particle size is independent of the ratio of incorporated Cd into the ZnCo2O4 matrix. The FT-IR transmission spectrum of each Cdx Zn1-xCo2O4 complex shows two strong vibration peaks that are ascribed to the spinel structure's octahedral and tetrahedral. The occurrence of light absorption by Cdx Znx-1 Co2O4 is due to the photoexcitation of electrons from O 2p to Co 3d transitions and d-d transition of Co 3d. The obtained values of the optical band gap (Eg) for Cdx Zn1-xCo2O4 varies from 2.93 eV for ZnCo2O4 (x = 0) to 2.15 eV for CdCo2O4 (x = 1).
SWIPT enabled UAV-RIS network using AI
Authors: Shrivastava Shriyanshu , Swami Pragya 
Published: September 2024

Abstract

The use of unmanned aerial vehicles (UAVs) has grown significantly in various fields, including surveillance, communication, and environmental monitoring. However, their flight endurance is restricted by the limitations of on-board batteries. To address this challenge, UAVs are integrated with reconfigurable intelligent surfaces (RIS) to implement energy harvesting (EH) using simultaneous wireless information and power transfer (SWIPT). This scheme facilitates the simultaneous transfer of both information and power to the UAV’s battery. A reliable deep reinforcement learning (DRL) based method has been used to enhance the performance of the proposed EH-RIS system in dynamic wireless environments. Results from the simulations demonstrated the superiority in the EH efficiency of the DRLbased EH-RIS system, achieving similar performance attained by exhaustive search. Softmax Deep Double Deterministic Policy Gradient (SD3) and Proximal Policy Optimization (PPO) are the different techniques used. Notably, the proposed PPO emerged as standout candidates, demonstrating superior performance in comparison to the others.
Modeling and field validation of the gravimetric composition of municipal solid waste disposed of in landfills
Authors: Bezerra Daniel Epifânio , Neto Cláudio Luis de Araújo , Ribeiro Libânia da Silva , Martildes Jéssica Araújo Leite , de Paiva William , Monteiro Veruschka Escarião Dessoles , de Melo Márcio Camargo 
Published: September 2024

Abstract

Gravimetric analysis of Municipal Solid Waste (MSW) stands as a fundamental procedure in landfill waste management. The characteristics of MSW are intricately shaped by various factors within a municipality, encompassing economy, climate, culture, education, and degree of urbanization. While the field implementation of gravimetric determination follows a relatively straightforward operational protocol, it remains a labor-intensive and financially demanding procedure. Additionally, it presents potential hazards of contamination to individuals involved in the screening process. Based on the foregoing, this research aims to compare the gravimetric composition of waste within a landfill situated in the semi-arid region of Brazil with its theoretical counterpart, derived from modeling through Artificial Neural Networks (ANN). Field characterization of the waste adhered to established technical standards, complemented by statistical planning for MSW collection and sampling. The assessment of theoretical composition was conducted using ANN models, with socioeconomic data serving as input variables and the gravimetric fractions of waste as outputs across various Brazilian municipalities. Multiple topologies were explored to identify an optimal configuration that yielded appropriate statistical validations. In general, the examination of both the empirical and theoretical gravimetric composition of MSW indicated a notable congruence between the datasets, thus emphasizing the effectiveness of mathematical modeling substantiated by statistical validations. Consequently, the utilization of mathematical modeling with ANN holds significant potential as a methodology for predicting the gravimetric composition of MSW. This approach efficiently mitigates environmental and health hazards while reducing financial expenditures and time constraints inherent in traditional methods.
Evaluation of endophytic bacteria for enhancing plant growth and its effect on the growth and productivity of betel leaf plants
Authors: Shabong Khamtilin , Kayang Highland 
Published: September 2024

Abstract

The aim of this research is to identify potent strains of endophytic bacteria from Piper betle L. that exhibit a wide range of in vitro plant growth-promoting (PGP) characteristics and to assess their effectiveness in promoting plant growth in vivo through greenhouse experiments. A total of 27 endophytic bacteria isolated from betel leaves were screened for PGP traits using both qualitative and quantitative methods. All bacterial isolates demonstrated positive results for IAA production, phosphate solubilization, ammonia production, siderophore production, pectinase activity, and HCN production. Specifically, the bacteria produced IAA in the range of 1.7 to 224.7 µg/ml, solubilized phosphate between 17.8 and 35.17 µg/ml, produced ammonia in concentrations of 0.14 to 0.51 µmol/ml, and exhibited siderophore production ranging from 38.92–71.9%. Four bacterial isolates, selected for their superior PGP traits, were identified through 16S rRNA gene analysis as Pseudomonas aeruginosa, Bacillus velezensis, Enterobacter cloacae, and Serratia marcescens. Among these, Pseudomonas aeruginosa showed the most significant enhancement of all growth parameters in betel plants under greenhouse conditions.
Potent and Selective SETDB1 Covalent Negative Allosteric Modulator Reduces Methyltransferase Activity in Cells
Authors: Frye Stephen , Uguen Melanie , Shell Devan , Silva Madhushika , Deng Yu , Li Fengling , Szewczyk Magdalena , Yang Ka , Zhao Yani , Stashko Michael , Norris Jacqueline , Waybright Jarod , Beldar Serap , Rectenwald Justin , Mordant Angie , Webb Thomas , Herring Laura , Arrowsmith Cheryl , Ackloo Suzanne , Gygi Steven , McGinty Robert , Barsyte-Lovejoy Dalia , Liu Pengda , Halabelian Levon , James Lindsey , Pearce Kenneth 
Published: September 2024

Abstract

A promising drug target, SETDB1, is a dual Kme reader and methyltransferase, which has been implicated in cancer and neurodegenerative disease progression. To help understand the role of the triple Tudor domain (3TD) of SETDB1, its Kme reader, we first identified a low micromolar small molecule ligand, UNC6535, which occupies simultaneously both the TD2 and TD3 reader binding sites. Further optimization led to the discovery of UNC10013, the first covalent 3TD ligand targeting Cys385 of SETDB1. UNC10013 is potent with a kinact/KI of 1.0 x 106 M-1s-1 and demonstrated proteome-wide selectivity. In cells, negative allosteric modulation of SETDB1-mediated Akt methylation was observed after treatment with UNC10013. Therefore, UNC10013 is a potent, selective and cell-active covalent ligand for the 3TD of SETDB1, demonstrating negative allosteric modulator properties and making it a promising tool to study the biological role of SETDB1 in disease progression.
A Bibliometric Taxonomy of Virtual Reality in Education: Global Trends and Key Challenges Across Multiple Indices and Leading Publishers
Authors: Samala Agariadne Dwinggo , Rawas Soha , Rahmadika Sandi , Criollo-C Santiago , Fikri Ryan , Sandra Randi Proska 
Published: September 2024

Abstract

The integration of technology in education has driven significant innovation, with virtual reality (VR) emerging as a powerful tool to enhance the learning experience. VR allows students to engage in immersive and interactive environments that go beyond traditional teaching methods, supporting visualization of complex concepts and experiential learning. Although VR has shown success in various disciplines such as medicine, engineering, and design, its applications in other fields remain unexplored. This study addresses this gap by conducting a comprehensive bibliometric analysis of VR in education, following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and utilizing multiple indexes in the Web of Science Core Collection and data from leading publishers. The analysis revealed key trends, such as Springer Nature's dominance in publishing VR-related research and the geographical distribution of VR studies, with the United States, China, and the United Kingdom as major contributors. Despite VR's potential, challenges such as high hardware costs, integration difficulties, and educator training needs hinder widespread adoption. The study also identifies potential solutions, including the development of affordable VR tools and better curriculum integration. The findings offer valuable insights for policymakers, educators, and technology developers, helping to guide more effective implementation and wider adoption of VR in diverse educational contexts.