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Monitoring reproductive physiology in wildlife can be a useful tool for assessing population dynamics for conservation and management purposes. Utilizing non-invasive approaches for this, such as quantifying reproductive hormone metabolites from faeces, can be challenging when defaecation events are not observed, or when cryptic species like African clawless otters (Aonyx capensis) are involved. Additionally, test systems for quantifying hormone metabolites in a species for the first time must first be reliably validated prior to use. Our results indicate that Epiandrosterone and Progesterone EIAs are most suitable for determining fAM and fPM concentrations in African clawless otter spraints. The fAM:fPM ratio and respective thresholds are more reliable in sex identification compared to the separate use of individual hormone classes. Sex-related hormone metabolite concentrations remained comparable for up to 12hrs post-defaecation in both sexes.

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  We screened two androgen and two progestagen enzyme-immunoassays (EIAs) for suitability and reliable quantification of faecal androgen metabolites (fAM) and faecal progestagen metabolites (fPM) in African clawless otters.

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  We assessed whether the ratio of fAM:fPM concentrations can be used to assign sex to faecal samples from unknown individuals.

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  We tested the stability of fAM and fPM concentrations post-defaecation to determine the effects of environmental exposure and bacterial metabolism.

The decision-making process consists of finding the best solution to an analyzed problem. This search is carried out in the face of countless interactions when analyzing an alternative criterion by criterion, under which weights are assigned that distinguish the degree of importance they have for the decision-makers. The definition of weight for each criterion gives rise to three lines of thought on the subject. There are objective, subjective, and hybrid methods. This discussion concerns the degree to which experts define the criteria weights. Based on this discussion, we developed a hybrid method to integrate the Entropy and CRITIC methods with the PROMETHEE method, called EC-PROMETHEE. The innovation of this method is that the combination of the Entropy and CRITIC methods does not result in a single set of weights. In reality, the weights generated by each method are used to define each criterion's upper and lower limits. The range of weights generated for each criterion is emulated "n" times and builds a set of weights that are applied to the ranking definition process. The model generates "n" rankings, defining a single ranking. In this article, we demonstrate a step-by-step application of a tool developed in Python called EC-PROMETHEE and use it as an example of the problem of choosing rotary-wing airplanes for application in the military police service.

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  The method reduces discretion in determining the weights of the criteria;

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  The innovation lies in the use of a range of weights for criteria;

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  Consistency in defining the final ranking.

Waste from the fishing industry is disposed of in soils and oceans, causing environmental damage. However, it is also a source of valuable compounds such as chitin. Although chitin is the second most abundant polymer in nature, its use in industry is limited due to the lack of standardized and scalable extraction methods and its poor solubility. The deacetylation process increases its potential applications by enabling the recovery of chitosan, which is soluble in dilute acidic solutions. Chitosan is a polymer of great importance due to its biocompatible and bioactive properties, which include antimicrobial and antioxidant capabilities. Chitin extraction and its deacetylation to obtain chitosan are typically performed using chemical processes that involve large amounts of strongly acidic and alkaline solutions. To reduce the environmental impact of this process, extraction methods based on biotechnological tools, such as fermentation and chitin deacetylase, as well as emerging technologies, have been proposed. These extraction methods have demonstrated the potential to reduce or even avoid using strong solvents and shorten extraction time, thereby reducing costs.

Nevertheless, it is important to address existing gaps in this area, such as the requirements for large-scale implementation and the determination of the stoichiometric ratios for each process. This review highlights the use of biotechnological tools and emerging technologies for chitin extraction and chitosan production. These approaches truly minimize environmental impact, reduce the use of strong solvents, and shorten extraction time. They are a reliable alternative to fishery waste valorization, lowering costs; however, addressing the critical gaps for their large-scale implementation remains challenging.

Understanding the mechanical behavior of heterogeneous materials is becoming increasingly crucial across various fields, including aerospace engineering, composite materials development, geology, and biomechanics. While substantial literature exists on this topic, conventional methods often rely on commercial software packages. This study presents a framework for computed tomography (CT) scan-based finite element (FE) analysis of such materials using open-source software in most of the workflow.

Our work focuses on three key aspects:

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  Mesh generation that incorporates spatially varying mechanical properties and well-defined boundary conditions.

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  Validation of the FE results through comparison with digital image correlation (DIC) system measurements.

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  Open-source software utilization throughout the entire process, making it more accessible and cost-effective.

The porosity of hollow fiber membranes is an important property in the design of processes implementing membrane contactors as it is directly related to the effective surface available for mass transfer. Nevertheless, measuring the porosity requires most of the time complex experimental setup and some of the existing methods are questionable when applied to polymeric membrane materials. In this work, we adapted a method originally proposed to estimate the porosity of flat membranes, in order to estimate the porosity of hollow fiber membranes.

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  Some hydrophobic hollow fibers are put in contact with a non-wetting solvent inside a pycnometer. The mass of the system is measured.

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  The process is repeated using a wetting solvent.

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  The porosity is deduced from the difference between the weighing data.

Screening strategies for GMO detection in food and feed are a crucial aspect in GMO testing laboratories for streamlining the analytical workflow and reducing turnaround time and costs. These strategies can be more or less complex or even be targeted according to the ingredients in the product, but whatever the choice, a good basic approach is generally based on the search for 35S promoter (P35S), nos-terminator (T-nos) and FMV promoter (P-FMV). In this study, we compare the singleplex real time PCR method for P35S, T-nos and P-FMV detection currently adopted by the Italian National Reference Laboratory for GM food and feed (NRL) with three commercial kits available on the market for giving a greater choice to consider the best approach suitable to the official control laboratories that are different from each other.

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  The NRL optimized singleplex PCR methods and the three commercial kits fully respect all the validation parameters criteria according to the minimum performance requirements (MPR) of ENGL [1]

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  Screening strategies for GMO detection in food and feed are a crucial aspect in GMO testing laboratories and being the commercial kits different from each other, the laboratory can choose the methods best suit their needs reducing turnaround time and costs.

Our article explores a variety of modern research techniques employed in neuroanatomy and neurophysiology. We highlight the use of computer technologies, image analysis methods, and innovative approaches that expand our understanding of anatomical structures. The techniques we discuss include fractal analysis, the Pickworth method, scanning microscopy, and advanced computer image processing systems. Fractal analysis, in particular, offers a unique perspective on brain structures and functions and is a key tool in neuroanatomical research. We also focus on its application in neuroanatomical studies, particularly in cases of Alzheimer's disease and epilepsy.

These modern research methods not only enhance our knowledge but also have significant clinical potential. Their use in diagnosing neurological diseases like Alzheimer's and epilepsy promises faster and more accurate diagnoses. We emphasize the combination of multiple methods for improved quality of anatomical structure imaging.

This paper presents a novel information generation methodology to support safer cycling patterns in urban environments, leveraging for that Large Language Models (LLMs), AI-based agents, and open geospatial data. By processing multiple files containing previously computed urban risk levels and existing mobility infrastructure, which are generated by exploiting open data sources, our method exploits multi-layer data preprocessing procedures and prompt engineering to create easy-to-use, user-friendly assistive systems that are able to provide useful information concerning cycling safety. Through a well-defined processing pipeline based on Data Ingestion and Preparation, Agents Orchestration, and Decision Execution methodological steps, our method shows how to integrate open-source tools and datasets, ensuring reproducibility and accessibility for urban planners and cyclists. Moreover, an AI agent is also provided, which fully implements our method and acts as a proof-of-concept implementation. This paper demonstrates the effectiveness of our method in enhancing cycling safety and urban mobility planning.

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  A novel method that combines LLMs and AI agents is defined to enhance the processing of multi-domain open geospatial data, potentially promoting cycling safety.

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  It integrates urban risk data and cycling infrastructure for a more comprehensive understanding of cycling resources, which become accessible by textual or audio prompts.

This paper introduces the ‘Australian Park Life Project’ and describes a protocol to standardise the capture and collation of public open greenspace spatial data across Australian cities. This method will progress greenspace research allowing for unique coherent national analyses and comparative research across Australia. We also outline the development of the Park Life public participatory geographic information system (PPGIS) to spatially explore what, and how, public open greenspaces are being used by Australian communities. The combination of community crowdsourced spatial data providing location-specific information on the green public open spaces used, in combination with the national spatial layer of greenspace allows for unique analyses exploring the role of greenspace provision and design on use and represents a transformative strategy in shaping public open space policy and strategy.

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  A spatial layer of public open greenspace was created for the eight Australian State and Territory capital cities using a standardised data capture and collection method from local government planning schemes and land use data, and listings of managed and demarcated parks and reserves.

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  The Park Life public participatory geographic information system (PPGIS) was built to capture spatially referenced information on the use of greenspaces - specifically what spaces are used, and how they are used.