Search Results (30)

In response to the growing market demand for Litopenaeus vannamei, a variety of single-species, high-density, intensive, and high-yield aquaculture modes have arisen. These aquacultural systems are teeming with microorganisms, which play roles in water quality and host health. To uncover the prokaryotic community composition across cultivation modes, we investigated the prokaryotic community composition at two fractionated sizes in the water of three culture modes of Litopenaeus vannamei, including high-level pond culture, biofloc technology (BFT), and pond culture. The 16S rRNA gene high-throughput sequencing results indicated that the taxa particularly enriched by high-level pond culture modes were mainly Deltaproteobacteria, while Alpha- and Gammaproteobacteria and Flavobacteria were enriched in the BFT culture modes. The pond culture enriched Bacteroidetes, Sphingobacteriia, Actinobacteria, and Cyanobacteria. PCoA analysis showed that for the pond samples, there were significant differences in the community composition compared with the samples from the other two modes. However, the high-level pond and biofloc samples showed similar community compositions. Furthermore, Canonical Correspondence Analysis (CCA) and Variance Partitioning Analysis (VPA) revealed that NH₄⁺-N, salinity (Sal), and NO₃⁻-N were key factors affecting the aquaculture communities. Full article

The study investigates controlled environment agriculture (CEA) in Nigeria focusing on its feasibility, economic benefits, environmental impact, and socio-economic implications. While CEA technologies such as hydroponics, vertical farming, automation, and greenhouse systems offer efficiency and yield improvements, this review highlights the extent to which they can be utilized in solving the food challenges facing the country including food shortages, wasteful use of land, and climatic disturbances in agriculture. However, their adoption faces challenges like high initial costs, technical knowledge gaps, and unstable energy infrastructure. Additionally, there is a lack of localized research on resource utilization, crop profitability, and the scalability of these systems in Nigeria’s urban and rural contexts, which further hinders adoption. Government policy reforms, renewable energy access, and capacity-building programs are crucial to overcoming these barriers. Localized pilot projects and field studies are also necessary to validate the feasibility of CEA systems under Nigeria’s unique socio-economic and climatic conditions. Cross-country comparisons with South Africa and Kenya reveal actionable insights for Nigeria’s CEA implementation such as South Africa’s public-private partnerships and Kenya’s solar-powered vertical farms which can serve as actionable blueprints for Nigeria’s CEA adoption and expansion. Nigeria with its teeming population is food import-dependent, with agricultural imports reaching 3.35 trillion Naira between 2019 and 2023. This is unsustainable and requires alternative measures including targeted CEA interventions to increase its agricultural productivity. Overall, for CEA to contribute meaningfully to the Nigerian agricultural sector, specific changes including targeted subsidies, policy reforms, renewable energy access, stakeholder engagement, capacity-building programs, and infrastructure development must be instituted to achieve sustainable agricultural growth. Furthermore, strategies such as hybridizing traditional and CEA practices and creating “pay-as-you-grow” financial models for CEA infrastructure can make the transition more viable for smallholder farmers, who dominate Nigeria’s agricultural sector. Full article

The phyllosphere, comprising the aerial portions of plants, is a vibrant ecosystem teeming with diverse microorganisms crucial for plant health and productivity. This review examines the functional roles of phyllosphere microorganisms in rice (Oryza sativa), focusing on their importance in nutrient uptake, disease resistance, and growth promotion. The molecular mechanisms underlying these interactions are explored along with their potential applications in enhancing sustainable rice production. The symbiotic relationships between rice plants and their associated microorganisms are highlighted, offering insights into improved agricultural practices. Furthermore, this review addresses the challenges and future developments in translating laboratory findings into practical applications. By synthesizing current research, this comprehensive analysis serves as a valuable resource for leveraging phyllosphere microbes in rice farming and related fields. Full article

Animal venoms are intricate and teem with potential for groundbreaking medical advancements. Although traditional methods for purifying venom proteins are effective, they usually require complicated, multi-step processes that lead to lower yields. Our study introduces an efficient, one-step technique for extracting venom-derived proteins through reverse-phase high-performance liquid chromatography (RP-HPLC). We carefully optimized the RP-HPLC process, focusing on the gradient elution conditions and the strategic use of our columns’ stationary phase characteristics, to enhance the effectiveness of our separations. This enabled us to efficiently isolate six venom proteins: melittin (2.846 kDa) from Apis mellifera with a yield of 4.5% and homogeneity of 99%; α-cobratoxin (7.821 kDa) from Naja kaouthia with a yield of 15% and homogeneity of 99%; α-bungarotoxin (7.983 kDa) from Bungarus multicinctus with a yield of 7% and purity of 99%; calciseptine (7.035 kDa) from Dendroaspis polylepis with a yield of 6% and homogeneity of 95%; notexin (13.593 kDa) from Notechis scutatus with a yield of 10% and homogeneity of 95%; and CVFm (150 kDa) from Naja melanoleuca with a yield of 0.8% and homogeneity of 94%. These were all accomplished in one step. This breakthrough simplifies the purification of venom peptides and proteins, making the process more feasible and economical. It paves the way for developing new drugs and promising treatments that are both more effective and precisely targeted. Full article

With a view to maintaining the reputation of wine-producing regions among consumers, minimising economic losses caused by wine fraud, and achieving the purpose of data-driven terroir classification, the use of an absorbance–transmission and fluorescence excitation–emission matrix (A-TEEM) technique has shown great potential based on the molecular fingerprinting of a sample. The effects of changes in wine composition due to ageing and the stability of A-TEEM models over time had not been addressed, however, and the classification of wine blends required investigation. Thus, A-TEEM data were combined with an extreme gradient boosting discriminant analysis (XGBDA) algorithm to build classification models based on a range of Shiraz research wines (n = 217) from five Barossa Valley sub-regions over four vintages that had aged in bottle for several years. This spectral fingerprinting and machine learning approach revealed a 100% class prediction accuracy based on cross-validation (CV) model results for vintage year and 98.8% for unknown sample prediction accuracy when splitting the wine samples into training and test sets to obtain the classification models. The modelling and prediction of sub-regional production area showed a class CV prediction accuracy of 99.5% and an unknown sample prediction accuracy of 93.8% when modelling with the split dataset. Inputting a sub-set of the current A-TEEM data into the models generated previously for these Barossa sub-region wines yielded a 100% accurate prediction of vintage year for 2018–2020 wines, 92% accuracy for sub-region for 2018 wines, and 91% accuracy for sub-region using 2021 wine spectral data that were not included in the original modelling. Satisfactory results were also obtained from the modelling and prediction of blended samples for the vintages and sub-regions, which is of significance when considering the practice of wine blending. Full article

While much existing research investigates embodiment and body image in individualised terms, new research in youth studies takes a wider view. How are young people’s experiences of embodiment entangled with sociocultural and structural influences? How do young people come to develop a sense of embodied identity in contexts that teem with hostile and unattainable body ideals? How are possibilities for affirming and affirmative embodiment navigated by young people—especially those living outside prevailing appearance norms? In this paper, we engage with these questions, drawing insights from an in-depth, collaborative research project designed to understand what supports and constrains hauora and wellbeing for young people in Aotearoa (New Zealand). First, we analyse young people’s accounts thematically, identifying three prevailing systems of cultural privilege that regulate embodiment. These include processes of racialisation and gendering, as well as cisnormative, heteronormative, ableist and healthist logics. Second, we work closely with one young person’s interview, exploring how her narrative unsettles prevailing norms of appearance and embodiment. By spotlighting what young people themselves tell us about their bodies and embodied experiences, this paper demonstrates the value of an embodiment lens for youth and wellbeing studies. Full article

In the present protocol, we determined the presence and concentrations of bisphenol A (BPA) spiked in surface water samples using EEM fluorescence spectroscopy in conjunction with modelling using partial least squares (PLS) and parallel factor (PARAFAC). PARAFAC modelling of the EEM fluorescence data obtained from surface water samples contaminated with BPA unraveled four fluorophores including BPA. The best outcomes were obtained for BPA concentration (R² = 0.996; standard deviation to prediction error’s root mean square ratio (RPD) = 3.41; and a Pearson’s r value of 0.998). With these values of R² and Pearson’s r, the PLS model showed a strong correlation between the predicted and measured BPA concentrations. The detection and quantification limits of the method were 3.512 and 11.708 micro molar (µM), respectively. In conclusion, BPA can be precisely detected and its concentration in surface water predicted using the PARAFAC and PLS models developed in this study and fluorescence EEM data collected from BPA-contaminated water. It is necessary to spatially relate surface water contamination data with other datasets in order to connect drinking water quality issues with health, environmental restoration, and environmental justice concerns. Full article

Networking protocols have undergone significant developments and adaptations to cater for unique communication needs within the IoT paradigm. However, meeting these requirements in the context of vehicle-to-infrastructure (V2I) communications becomes a multidimensional problem due to factors like high mobility, intermittent connectivity, rapidly changing topologies, and an increased number of nodes. Thus, examining these protocols based on their characteristics and comparative analyses from the literature has shown that there is still room for improvement, particularly in ensuring efficiency in V2I interactions. This study aims to investigate the most viable network protocols for V2I communications, focusing on ensuring data quality (DQ) across the first three layers of the IoT protocol stack. This presents an improved understanding of the performance of network protocols in V2I communication. The findings of this paper showed that although each protocol offers unique strengths when evaluated against the identified dimensions of DQ, a cross-layer protocol fusion may be necessary to meet specific DQ dimensions. With the complexities and specific demands of V2I communications, it’s clear that no single protocol from our tri-layered perspective can solely fulfil all IP-based communication requirements given that the V2I communication landscape is teeming with heterogeneity, where a mixture of protocols is required to address unique communication demands. Full article

The field of soft matter teems with molecules and aggregates of molecules that have internal size-modulating degrees of freedom. Proteins, peptides, microgels, polymers, micelles, and even some colloids can exist in multiple—often just two dominating—states with different effective sizes, where size can refer to the volume or to the cross-sectional area for particles residing on surfaces. The size-dependence of their accessible states renders the behavior of these particles pressure-sensitive. The Bragg–Williams model is among the most simple mean-field methods to translate the presence of inter-particle interactions into an approximate phase diagram. Here, we extend the Bragg–Williams model to account for the presence of particles that are immersed in a solvent and exist in two distinct states, one occupying a smaller and the other one a larger size. The basis of the extension is a lattice–sublattice approximation that we use to host the two size-differing states. Our model includes particle–solvent interactions that act as an effective surface tension between particles and solvent and are ignorant of the state in which the particles reside. We analyze how the energetic preference of the particles for one or the other state affects the phase diagrams. The possibility of a single phase-two phases-single phase sequence of phase transitions as a function of increasing temperature is demonstrated. Full article

Healthy soil biota is the key to meeting the world population’s growing demand for food, energy, fiber and raw materials. Our aim is to investigate the effect of green manure as a strategy to recover the macrofauna and the chemical properties of soils which have been anthropogenically degraded. The experiment was a completely randomized block design with four replicates. Green manure, Urochloa decumbens, with or without application of limestone and gypsum, composed the integrated systems. The macroorganisms as well as the soil fertility were analyzed after 17 years of a process of soil restoration with the aforementioned systems. The succession of Stizolobium sp. with Urochloa decumbens, with limestone and gypsum, was teeming with termites, beetles and ants. This integrated system presented the most technically adequate indexes of diversity and uniformity. Multivariate models showed a substantial increase in the total number of individuals due to the neutralization of harmful elements and the gradual release of nutrients by limestone and plaster. These conditioners have undergone multiple chemical reactions with the substrate in order to balance it chemically, thus allowing the macroinvertebrates to grow, develop, reproduce and compose their food web in milder microclimates. It was concluded that the integration of green manure together with grass is an economical and environmentally correct strategy to restore the macrofauna properties of degraded soil in the Brazilian savannah. Full article

Generations of sensors have been developed for predicting food sensory profiles to circumvent the use of a human sensory panel, but a technology that can rapidly predict a suite of sensory attributes from one spectral measurement remains unavailable. Using spectra from grape extracts, this novel study aimed to address this challenge by exploring the use of a machine learning algorithm, extreme gradient boosting (XGBoost), to predict twenty-two wine sensory attribute scores from five sensory stimuli: aroma, colour, taste, flavour, and mouthfeel. Two datasets were obtained from absorbance-transmission and fluorescence excitation-emission matrix (A-TEEM) spectroscopy with different fusion methods: variable-level data fusion of absorbance and fluorescence spectral fingerprints, and feature-level data fusion of A-TEEM and CIELAB datasets. The results for externally validated models showed slightly better performance using only A-TEEM data, predicting five out of twenty-two wine sensory attributes with R² values above 0.7 and fifteen with R² values above 0.5. Considering the complex biotransformation involved in processing grapes to wine, the ability to predict sensory properties based on underlying chemical composition in this way suggests that the approach could be more broadly applicable to the agri-food sector and other transformed foodstuffs to predict a product’s sensory characteristics from raw material spectral attributes. Full article

When describing the behaviour and modelling of real systems, which are characterized by considerable complexity, great difficulty, and often the impossibility of their formal mathematical description, and whose operational monitoring and measurement are difficult, conventional analytical–statistical models run into the limits of their use. The application of these models leads to necessary simplifications, which cause insufficient adequacy of the resulting mathematical description. In such cases, it is appropriate for modelling to use the methods brought by a new scientific discipline—artificial intelligence. Artificial intelligence provides very promising tools for describing and controlling complex systems. The method of neural networks was chosen for the analysis of the lifetime of the teeming ladle. Artificial neural networks are mathematical models that approximate non-linear functions of an arbitrary waveform. The advantage of neural networks is their ability to generalize the dependencies between individual quantities by learning the presented patterns. This property of a neural network is referred to as generalization. Their use is suitable for processing complex problems where the dependencies between individual quantities are not exactly known. Full article

Literature is teeming with publications on industrial pollution. Over the decades, the main industrial pollutants and their effects on human health have been widely framed. Among the various compounds involved, benzene plays a leading role in the onset of specific diseases. Two systems are mainly affected by the adverse health effects of benzene exposure, both acute and chronic: the respiratory and hematopoietic systems. The most suitable population targets for a proper damage assessment on these systems are oil refinery workers and residents near refining plants. Our work fits into this area of interest with the aim of reviewing the most relevant cases published in the literature related to the impairment of the aforementioned systems following benzene exposure. We perform an initial debate between the two clinical branches that see a high epidemiological expression in this slice of the population examined: residents near petroleum refinery areas worldwide. In addition, the discussion expands on highlighting the main immunological implications of benzene exposure, finding a common pathophysiological denominator in inflammation, oxidative stress, and DNA damage, thus helping to set the basis for an increasingly detailed characterization aimed at identifying common molecular patterns between the two clinical fields discussed. Full article

Environmental, cultural, and social issues are becoming increasingly complex, and the educational context is no exception to this trend. The relevance of teachers’ creativity in examining situations from different angles, in imagining new approaches, in adapting to the varied needs of students, and in training them so that they too can grasp the teeming complexity seems obvious. However, creativity sometimes seems to be taken for granted among teachers and educational programs leave a gap around this theme. Since the scientific literature tends to show that teachers’ creativity is still little explored in educational contexts, this doctoral research studies its manifestations within a group of teachers enrolled in a professional master’s program in preschool and elementary education (Université de Sherbrooke, Canada). Within the framework of this program, each one elaborates a professional development project over a three-year period. Using a variety of authentic data sources (observations in natural occurring situations, reflective writing by participants, and semi-structured interviews), their creative process is documented and analyzed. This multiple-case study (n = 9) that draws on the concept of creativity as related to that of professional coherence reveals that the pursuit of greater professional coherence not only enables the implementation of creative skills to foster teachers’ professional development, but also elicits beautiful risk-taking. Full article