bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dual‐Mode Nanoprobes Based on Lanthanide Doped Fluoride Nanoparticles Functionalized by Aryl Diazonium Salts for Fluorescence and SERS Bioimaging
Authors: Chen Huan , Nizard Philippe , Decorse Philippe , Nowak Sophie , Ammar‐Merah Souad , Pinson Jean , Gazeau Florence , Mangeney Claire , Luo Yun 
Published: October 2023

AbstractThe design of dual‐mode fluorescence and Raman tags stimulates a growing interest in biomedical imaging and sensing applications as they offer the possibility to synergistically combine the versatility and velocity of fluorescence imaging with the specificity of Raman spectroscopy. Although lanthanide‐doped fluoride nanoparticles (NPs) are among the most studied fluorescent nanoprobes, their use for the development of bimodal fluorescent‐Raman probes has never been reported yet, to the best of the authors knowledge, probably due to the difficulty to functionalize them with Raman reporter groups. This gap is filled herein by proposing a fast and straightforward approach based on aryl diazonium salt chemistry to functionalize Eu3+ or Tb3+ doped CaF2 and LaF3 NPs by Raman scatters. The resulting surface‐enhanced Raman spectroscopy (SERS)‐encoded lanthanide‐doped fluoride NPs retain their fluorescence labeling capacity and display efficient SERS activity for cell bioimaging. The potential of this new generation of bimodal nanoprobes is assessed through cell viability assays and intracellular fluorescence and Raman imaging, opening up unprecedented opportunities for biomedical applications.
Magnetic Removal of Micro‐ and Nanoplastics from Water—from 100 nm to 100 µm Debris Size
Authors: Gaß Henrik , Kloos Tonya M. , Höfling Anna , Müller Lukas , Rockmann Linda , Schubert Dirk W. , Halik Marcus 
Published: October 2023

AbstractClean water is one of the most important resources of the planet but human‐made contamination with diverse pollutants increases continuously. Microplastics (<5 mm diameter) which can have severe impacts on the environment, are present worldwide. Degradation processes lead to nanoplastics (<1 µm), which are potentially even more dangerous due to their increased bioavailability. State‐of‐the‐art wastewater treatment plants show a deficit in effectively eliminating micro‐ and nanoplastics (MNP) from water, particularly in the case of nanoplastics. In this work, the magnetic removal of three different MNP types across three orders of magnitude in size (100 nm–100 µm) is investigated systematically. Superparamagnetic iron oxide nanoparticles (SPIONs) tend to attract oppositely charged MNPs and form aggregates that can be easily collected by a magnet. It shows that especially the smallest fractions (100–300 nm) can be separated in ordinary high numbers (1013 mg−1 SPION) while the highest mass is removed for MNP between 2.5 and 5 µm. The universal trend for all three types of MNP can be fitted with a derived model, which can make predictions for optimizing SPIONs for specific size ranges in the future.
Determining the dimension of weighted inverse regression ensemble
Authors: Chen Yinfeng , Li Lu , Yu Zhou 
Published: October 2023

SummarySliced inverse regression (SIR) has propelled sufficient dimension reduction (SDR) into a mature and versatile field with wide‐ranging applications in statistics, including regression diagnostics, data visualisation, image processing and machine learning. However, traditional inverse regression techniques encounter challenges associated with sparsity arising from slicing operations. Weighted inverse regression ensemble (WIRE) presents a novel slicing‐free approach to SDR. In this paper, we establish the asymptotic test theory to determine the dimension as estimated by WIRE. Moreover, we propose a permutation‐based method for determining the order. Extensive numerical studies and real data analysis confirm the excellent performance of the proposed order determination method based on WIRE.
Characterization and stability assessment of Ocimum gratissimum leaves extract loaded nanostructured lipid carrier
Authors: Nasir Najaa Fadhilah Mohd , Hasham Rosnani , Sabtu Rahimah , Ali Fathilah , Adrus Nadia , Jamaluddin Jamarosliza , Rahman Roshanida Abdul , Hamid Mariani Abdul , Yaakob Harisun 
Published: October 2023

AbstractIn the last few decades, several nanoparticles technologies of actives delivery systems have emerged in the formulation of personal care products. The purpose of this study is to formulate the nanostructured lipid carrier loaded with Ocimum gratissimum leaves extract (OGNLC) and to characterize the chemical and physical properties of the OGNLC formulation. Ultrasound‐Assisted Extraction (UAE) method are used in this study to obtain O. gratissimum extract with the determination of the TPC, while melt emulsification homogenization conjoined with ultrasonic homogenization method are used to prepare OGNLC samples. Two types of surfactants (Tween 80 and soy lecithin) are incorporated in the formulation to form OGNLC with various compositions (%) to determine the best formulation. The effect of varying compositions of surfactants in OGNLC samples on the mean particle size (MPS), polydispersity index (PDI), zeta potential (ZP) and encapsulation efficiency (EE%) of OGNLC are characterized. The best formulation also was analyzed by FTIR spectroscopy, and the encapsulation efficiency are determined. The stability of OGNLC particle size was also assessed after 30 days of exposure under low and room temperature (4°C, 25°C). An optimal OGNLC consists of 2.0% O. gratissimum extract, 2.0% GMS, 10.0% VCO, and varying surfactant compositions of 2.0% of Tween 80, and 1.0% of soy lecithin by a mean particle size of 155.73 ± 1.53 nm, a PDI value of 0.203 ± 0.007, zeta potential of |−37.2| ± 0.95 mV, and encapsulation efficiency (%) of 95.70% ± 6.256%. The stability assessment of OGNLC showed that the obtained formulation is at least stable for more than 30 days. This study concludes that the composition of surfactants are important factors affecting the size and stability of the OGNLC. This is the first study to report on the synthesis of nanostructured lipid carrier loaded with O. gratissimum.
Effect of air pollution on plant secondary metabolites in selected trees of Delhi
Authors: Lahiri Milinda , Krishna Kalyani 
Published: October 2023

AbstractAir pollution is emerging as one of the most important stresses, particularly in urban areas, of both developed and developing countries. It severely affects plant growth and development besides being a health hazard to humans and animals. Delhi has the dubious distinction of being one of the most polluted cities in the world. Incidentally, it is also one of the greenest cities with ongoing programs to increase the already considerable forest cover and biodiversity parks. Plants often act as a sink for airborne pollutants, including particulate matter. Hence it is important to evaluate their efficacy in absorbing pollutants and use the promising species for urban plantation. In the present study, the stress tolerance of four common trees of Delhi (Psidium guajava, Alstonia scholaris, Murraya koenigii, and Moringa oleifera), growing in three areas with varying pollution levels, was estimated by measuring Plant Secondary Metabolites (PSMs: total phenols, flavonoids, alkaloids, and tannins) along with the total chlorophyll content of the leaves. P. guajava showed significant increase in the contents of phenols, tannins, and alkaloids with higher Air Quality Index (AQI). Increased amounts of phenols and flavonoids were observed in A. scholaris, those of phenols and alkaloids in M. koenigii, and only of alkaloids in M. oleifera. There was a decrease in the total chlorophyll content of the leaves of all four species investigated. P. guajava and A. scholaris can be recommended for plantation along the sides of roads with heavy traffic movement. Since PSMs are seen to accumulate as a defense mechanism against air pollution too, as in various abiotic and biotic stresses, they can be used as biomarkers for stress tolerance in plants.
Synergistic flame retardant modification of bio‐based nylon 56 by graphitic carbon nitride and melamine cyanurate
Authors: Wang Zihao , Wang Jinheng , Zhang Jianting , Guo Weihong 
Published: October 2023

AbstractTo address the flammability drawbacks of nylon 56 and expand the application range of bio‐based nylon 56, melamine cyanurate (MCA) was employed through self‐assembly in a solvent with graphitic carbon nitride surface treatment. Modified MCA (CNMCA)composition and morphology were investigated. CNMCA created with surface treatment and polyamide 56 (PA56) prepared with unmodified MCA had their flame retardant functions and mechanical properties investigated and compared. x‐ray diffraction (XRD) and Fourier transform infrared (FT‐IR) spectroscopy confirmed the successful microencapsulation of g‐C3N4 on the MCA surface. Further characterization of the unmodified MCA and CNMCA was performed using scanning electron microscopy (SEM). The SEM images revealed a significant reduction in the degree of agglomeration in CNMCA compared to conventional MCA, resulting in a more uniform dispersion in the PA56 matrix. Additionally, PA56/CNMCA achieved a UL94 V‐0 rating and a limiting oxygen index (LOI) value of 30.1%. Notably, compared to pure PA56, PA56/CNMCA30 exhibited the most promising synergistic effect, leading to a separate reduction of 45.45% in the total heat release rate (THR) and 13.62% in the total smoke release (TSR). Consequently, with the same flame retardant addition (10 wt%), the CNMCA flame retardant showed superior dispersion in the bio‐based nylon 56 matrix compared to traditional MCA. Due to the physical isolation of g‐C3N4, the synergistic effect of MCA and graphitic carbon nitride imparted better mechanical properties and flame resistance to nylon 56.Highlights
MCA/g‐C3N4 hybrids were prepared and applied in bio‐based nylon 56 for the first time.
The MCA/g‐C3N4 hybrid has better dispersion than MCA.
PA56/MCA/g‐C3N4 flame retardant composites have better flame retardant and smoke suppression properties than PA56/MCA.
Estimation of soil moisture using environmental covariates and machine learning algorithms in Cathedral Peak Catchment, South Africa
Authors: Kibirige Daniel Murungi Kironde , Gokool Shaeden , Mkhize Zama Nosihle 
Published: October 2023

AbstractSoil moisture (SM) is a fundamental constituent of the terrestrial environment and the hydrological cycle. Owing to its significant influence on catchment hydrological responses, it can be utilized as an indicator of floods and droughts to aid early warning systems. This study aimed to develop a field‐scale method to estimate SM using parametric and machine learning‐based methods to compare whether advanced artificial intelligence methods can give similar results as traditional methods. Considering this, monthly observed SM data (from the top 10 cm), environmental covariates, and remotely sensed data from March 2019 to July 2021 for the Cathedral Peak Research Catchments VI and IX in South Africa were obtained. From the 241 observations obtained across 12 sites, 160 (∼66%) were used for model training, while the remaining 81 (∼34%) were used for model testing. Employing 10‐fold cross‐validation, the individual machine learning models (viz., support vector machine [SVM], random forest (RF), k‐nearest neighbor, classification and regression trees [Rpart], and generalized linear model) displayed a satisfactory performance (R2 = 0.52–0.79; root mean square error = 3.79–5.80). In the validation phase, the RF model displayed a superior performance, followed by the SVM. Subsequent SM estimation using the hybrid model produced satisfactory results in training (R2 = 0.90) and testing (R2 = 0.45). The results obtained from this study can aid in predicting SM variations in catchments with limited monitoring. Furthermore, this model can be applied in drought monitoring, forecasting, and informing agricultural management practices.
Effect of four eggshell repair materials on weight loss during incubation of white leghorn chicken eggs
Authors: Byrne Patricia , Jensen Thomas , Kristan William , Theule Jessica , Durrant Barbara 
Published: October 2023

AbstractEgg weight loss during incubation is a key indicator used to monitor successful egg development and is closely related to hatchability and chick survival. Artificial incubation is one of the most important captive breeding techniques used in conservation efforts to bolster avian populations. To repair damage to the eggshell and ensure embryonic viability during incubation, a variety of repair coverings can be applied. This study tested the impact of four repair materials (nail polish, synthetic glue, medical dressing, and molten wax film) on egg weight loss during incubation. We found no impact on weight loss for coverings smaller than 35% of the eggshell surface, nor did we find any differences between covering types. The average egg weight loss decreased as the coverage area increased, and the weight loss did not differ when blunt versus sharp‐end coverings were compared. Given the relative insensitivity of egg weight loss and survival to the type of patch material used, we concluded that the selection of material for the purpose of weight loss management could be based on practical considerations, such as ease of application and availability.
De Rham prismatic crystals over $$\mathcal {O}_K$$
Authors: Liu Zeyu 
Published: October 2023

AbstractWe study de Rham prismatic crystals on "Equation missing". We show that a de Rham crystal is controlled by a sequence of matrices $$\{A_{m,1}\}_{m \ge 0}$$

{

A

m
,
1

}

m
≥
0

with $$A_{0,1}$$

A

0
,
1

“nilpotent”. Using this, we prove that the natural functor from the category of de Rham crystals over "Equation missing" to the category of nearly de Rham representations is fully faithful. The key ingredient is a Sen style decompletion theorem for $$B_{{\textrm{dR}}}^+$$

B

dR

+

-representations of $$G_K$$

G
K

.
Is there a role for aromatic plants in blue tit (Cyanistes caeruleus) nests? Results from a correlational and an experimental study
Authors: Garrido-Bautista Jorge , Ramos Jaime Albino , Arce Sofía Irene , Melero-Romero Pablo , Ferreira Rafael , Santos-Baena Carolina , Guímaro H. R. , Martín-Villegas Carlos , Moreno-Rueda Gregorio , Norte Ana Cláudia 
Published: October 2023

AbstractThe utility of fresh green material in avian nests is still not fully understood. Potential explanations include the effects of plants’ volatile compounds on parasite reduction (nest protection hypothesis) or direct beneficial effects on nestling condition (drug hypothesis). We used correlative data collected during 2020 and 2021 in a Mediterranean population of blue tits (Cyanistes caeruleus) as well as experimental data (aromatic nest content manipulation) to assess the effects of aromatic plant use on nestling physiological condition and survival, nest-dwelling ectoparasitic pressure and its relationship with breeding parameters. We found that aromatic plants were disproportionally used in relation to their abundance in the environment and that their use was positively related to egg mass (but only in 2020). Blowflies and facultative parasitic mites were more frequent in nests with aromatics compared to nests without aromatics, but obligatory parasitic mites were less abundant in nests with aromatics. However, no effects of aromatic plants were observed on nestling haemoglobin levels nor erythrocyte sedimentation rate or other physiological health metrics, but the heterophil to lymphocyte ratio was higher in nests with the highest quantity of aromatics. The artificial addition of mint reduced the flea abundance, but 7-day old nestlings showed significantly lower colour saturation and brightness in the mouth flange. Nestling survival to fledging was not related to aromatic plant use. Therefore, our results partially support a beneficial effect of aromatic plants in blue tit nests because some ectoparasite groups were reduced. Immediate effects on nestling physiology or survival could not be established.Significance statementSome avian species place fresh aromatic plant material in their nests, and several non-mutually exclusive hypotheses have been proposed to explain its potential functions. In this study, we use both correlational and experimental data from a blue tit population to test two hypotheses, namely the ‘nest protection hypothesis’ and the ‘drug hypothesis’. The first one proposes that aromatic plants have direct repellent effects against ectoparasites, while the latter poses that these plant components benefit nestling condition through the stimulation of some components of the immune system. Our results suggest that some ectoparasites, such as fleas and obligatory parasitic mites, were less abundant in nests where aromatic plants were artificially or naturally added, respectively, but no relationships were detected with nestling physiology or survival, which could be partially explained by our small sample size. Our study partially supports a beneficial effect of aromatic plants in avian nests.
Representing and extending ensembles of parsimonious evolutionary histories with a directed acyclic graph
Authors: Dumm Will , Barker Mary , Howard-Snyder William , DeWitt III William S. , Matsen IV Frederick A. 
Published: October 2023

AbstractIn many situations, it would be useful to know not just the best phylogenetic tree for a given data set, but the collection of high-quality trees. This goal is typically addressed using Bayesian techniques, however, current Bayesian methods do not scale to large data sets. Furthermore, for large data sets with relatively low signal one cannot even store every good tree individually, especially when the trees are required to be bifurcating. In this paper, we develop a novel object called the “history subpartition directed acyclic graph” (or “history sDAG” for short) that compactly represents an ensemble of trees with labels (e.g. ancestral sequences) mapped onto the internal nodes. The history sDAG can be built efficiently and can also be efficiently trimmed to only represent maximally parsimonious trees. We show that the history sDAG allows us to find many additional equally parsimonious trees, extending combinatorially beyond the ensemble used to construct it. We argue that this object could be useful as the “skeleton” of a more complete uncertainty quantification.
Water mixing processes in a complex multi-layer hydrosystem in southwestern Madagascar: a combined isotopic and piezometry approach
Authors: Carrière Simon D. , Rakotomandrindra Pascale F. M. , Heath Thomas , Chalikakis Konstantinos , Gillon Marina , Leblanc Marc , Tweed Sarah 
Published: October 2023

AbstractWater transfers through a multilayered aquifer system are difficult to characterize. This study explores whether the conceptual model of water mixing at depth can be extrapolated over a hydrosystem extended across several tens of kilometers and including multiple aquifer layers. The processes are investigated using a combination of isotope tracers and piezometric monitoring over 10 years. The goal of this approach is to better understand how water transfer occurs throughout a complex and poorly documented hydrosystem of the Mahafaly Plateau in southwestern Madagascar. The results show a clear smoothing of isotopic variability with depth, associated with a smoothing of the recharge peaks. Isotopic values are strongly variable in the near surface (from -6.8 to -2.5‰ 18O) and stabilize at a critical depth (near 20 m) at around -4.7‰ 18O. These results indicate high vertical flows through the aquifer system, where there is neither obvious dominant recharge via preferential pathways nor lateral mixing. Such a strong smoothing effect on groundwater isotopic variability with depth has been rarely observed so clearly over a large spatial scale. These results provide information on a remote groundwater flow system at a scale pertinent to groundwater resource assessment. The results also indicate that the Neogene aquifers of the Mahafaly Plateau are poorly connected with other water resources (rivers, old sedimentary formations) except for the percolation of water towards the deep Eocene karst. This means that groundwater resources in the Ankazomanga Basin are limited and that it is essential to understand and quantify recharge for sustainable groundwater management.
Can wells in the vadose zone be backflushed to regain infiltration capacity? Concept and laboratory test
Authors: Kalwa Fritz 
Published: October 2023

AbstractVadose zone wells (VZW), or drywells, allow for high infiltration rates combined with small area demand. Nevertheless, they are rarely used for managed aquifer recharge, since turbid water leads to gradual clogging and a reduction in infiltration capacity. Established redevelopment measures require backflushing, which is commonly considered impossible for VZWs, making them “non regenerable”. In this study, the possibility of backflushing a VZW is discussed. Key to the underlying approach is isolating the lower (clogged) section of a well and saturating its surrounding with water by infiltration via the upper (unclogged) screen. Subsequently, underpressure sucks water from the surrounding soil into the isolated section. The approach was tested with and without a gravel pack, on laboratory scale, showing a successful reversal of flow direction in both cases. The degree of redevelopment was quantified by measuring the drainage time of the well, which increased from initially 45 s without gravel pack and 40 s with gravel pack to 9,500 and 11,000 s, respectively, after clogging. After backflushing, the well with gravel pack showed a median drainage time of 95 s, which remained stable over ten cycles of clogging and backflushing. In contrast, drainage time of the well without gravel pack increased continuously to >170 s, even after vibrator application. In conclusion, it can be stated that the backflush of a VZW with the presented approach is possible and has an effect on the well’s infiltration capacity, though it seems more effective for wells with gravel pack.
Deep neural network techniques for monaural speech enhancement and separation: state of the art analysis
Authors: Ochieng Peter 
Published: October 2023

AbstractDeep neural networks (DNN) techniques have become pervasive in domains such as natural language processing and computer vision. They have achieved great success in tasks such as machine translation and image generation. Due to their success, these data driven techniques have been applied in audio domain. More specifically, DNN models have been applied in speech enhancement and separation to perform speech denoising, dereverberation, speaker extraction and speaker separation. In this paper, we review the current DNN techniques being employed to achieve speech enhancement and separation. The review looks at the whole pipeline of speech enhancement and separation techniques from feature extraction, how DNN-based tools models both global and local features of speech, model training (supervised and unsupervised) to how they address label ambiguity problem. The review also covers the use of domain adaptation techniques and pre-trained models to boost speech enhancement process. By this, we hope to provide an all inclusive reference of all the state of art DNN based techniques being applied in the domain of speech separation and enhancement. We further discuss future research directions. This survey can be used by both academic researchers and industry practitioners working in speech separation and enhancement domain.