MethodsX最新文献

Qualitative conceptual models are commonly used in the scientific literature to make complex phenomena easier to understand. However, the effectiveness and usability of conceptual models to serve as analytical tools is rarely explored and tested, and there is a lack of guidelines for such analyses. This paper adapts and combines the methods of usability testing and cross-case analysis to describe a systematic protocol to facilitate the qualitative evaluation of conceptual models. Usability testing is an established method for identifying problems or shortcomings within a product and for assessing different dimensions of product usability: suitability, accessibility, relevance, and integrity. Cross-case analysis, on the other hand, is a qualitative research method for systematically comparing information from individual case studies and identifying commonalities and patterns that apply across cases. Taken together, these methodological approaches provide a structured way of retrospectively applying a conceptual model to existing literature and thereby evaluating its effectiveness in meeting its intended purpose.

• •

  We show how researchers can prepare, conduct, and synthesise the results of a usability test of a conceptual model.

• •

  We provide recommendations for the practical implementation of each step.

• •

  We outline the benefits, limitations, and ethical considerations that researchers should be aware of.

In 2015, a marine mesocosm facility was designed and implemented by the Coral Vivo Project in its research station (Porto Seguro, Bahia State, Brazil) to initially study the effects of global impacts, especially ocean warming and acidification, on coral reefs. However, local impacts, including seawater contamination with metal(loid)s, are considered as a major threat to coral reefs. Also, in 2015, the largest disaster involving a mining dam occurred in Brazil. Iron (Fe) mining tailings originated from the dam failure affected not only freshwater ecosystems (rivers, lakes and lagoons), but also adjacent beaches, mangroves, restingas, reefs and other marine systems. Seawater, sediments and biota were contaminated with metal(loid)s, especially Fe, arsenic (As), mercury (Hg) and manganese (Mn). Therefore, we aimed to adapt the marine mesocosm facility of the Coral Vivo Project to evaluate the bioaccumulation and biological impacts of increasing concentrations of dissolved Fe on a diversity of reef organisms. Results obtained indicate a great versatility and reliability of the marine mesocosm system for application in biological and ecological studies on the isolated effect of seawater dissolved Fe on reef organisms of different functional groups simultaneously.

• •

  Studies involving seawater enrichment with dissolved Fe can be performed using a marine mesocosm system.

• •

  The marine mesocosm is a reliable tool to study the isolated effects of metal(loid)s on reef organisms.

This paper provides a novel and applicable work that builds a real system for disinfecting the air and surfaces of the environment in a hospital room, with a non-contact measurement system for supporting contagious disease treatments in hospitals. The system is built on an intelligent mobile robot system that operates autonomously in a simulated real treatment room. The research team uses a new positioning algorithm. It is a combination of data from the Lidar sensor, encoder, and Extended Kalman filter. The program that applies segmentation and image feature extraction algorithms is developed to meet requirements of real-time environment mapping in the room. Control algorithms for moving and avoiding obstacles are also proposed. Next, techniques for collecting health data including patient identification, body temperature, and blood oxygen index via wireless sensor network are also mentioned in the article. Analysis and experimental results show qualified outcomes and promise. The main contribution of the paper can be listed as follows.

• •

  Design and build a new CEE-IMR, an intelligent mobile robot that can regconize patients, guide and lead them walking in hospitals, especially keep a safe distance avoiding contagious deseases.

• •

  A novel framework for controlling the robot is proposed. The robot can move flexible, avoid obstacles, etc. based on advanced control algorithms. A new control mechanism is also proposed.

• •

  Methods of collecting data and processing medical data to support either patients or doctors to improve the effecency in hospitals in contagious disease management.

This research study synthesized a base catalyst from the waste Citrullus lanatus rind (WCLR) for the synthesis of biodiesel from the waste pig fat oil. The high-acid-value oil (high free fatty acid: FFA) was converted to low-acid-value oil through adsorption in sorghum bagasse ash with high particle sizes. The developed base catalyst was obtained from the WCLR and was characterized via thermogravimetric analysis (TGA), Scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM/EDX), Fourier Transform Infrared Spectroscopy (FTIR), X-ray diffraction (XRD-FT), and Brunauer-Emmett-Teller (BET) adsorption analysis. The properties of biodiesel were compared with the recommended standard.

Results reflected that the duroc breed pig fat is rich in oil, and the oil is unsaturated. Sorghum bagasse proved to be a good bio-adsorbent for the unsaturated fat FFA reduction. The catalyst produced from WCLR was found to be rich in potassium-calcium-magnesium (K-Ca-Mg) base salts. The predicted yield of 98.69 % (wt./wt.) at 69.96 min, 79.93 °C, 3.15 % (wt.), and 8.57 (vol.) at desirability of 100 % was validated as 98.52 % (wt./wt.). Catalytic strength can be recycled in five cycles. The cost implications indicated that the cost of producing 25 L of biodiesel is $2.61.

This study proved to be the most economical way of producing biodiesel that is environmentally friendly, cost-effective, and easy to produce for future energy needs.

• •

  Oil was obtained via rendering from duroc breed waste fat oil.

• •

  Sorghum bagasse was used as adsorbent for acid reduction of high FFA pig fat oil.

• •

  Base catalyst used was obtained from calcined waste Citrullus lanatus rind.

This study optimized a gas chromatography-tandem triple quadrupole mass spectrometry (GC-MS/MS) method for the determination of 21 persistent organic pollutants (POPs) in Irtysh River water, including 14 organochlorines (OCPs) and 7 polychlorinated biphenyls (PCBs). Factors such as column temperature ramping, selection of qualitative and quantitative ion pairs and collision energy were considered to achieve perfect separation and accurate quantification of all 21 target compounds. The limits of detection (LOD) for PCBs and OCPs ranged from 0.21 to 1.18 ng/L. Applying this method to detect POPs in the Irtysh River revealed concentrations of OCPs ranging from ND to 20.2 ng/L and PCBs from ND to 0.411 ng/L. Source analysis indicated that POPs in the Irtysh River mainly originate from historical industrial and agricultural activities, particularly the deliberate use of pesticides. To ensure ecological safety and human health, expanding the range of target analytes and monitoring periods is necessary. This study provides:

• •

  Qualitative and quantitative analysis methods for 7 PCBs and 14 OCPs.

• •

  Recoveries achieved ranged between 74.6 to 109 % with RSD less than 15 %.

• •

  Analysis of sources, transport pathways, accumulation status, and ecological risks of PCBs and OCPs in the Irtysh River.

This study introduces a ground-breaking approach, the Whale Optimization Algorithm (WOA)-based multivariate exponential smoothing Grey-Holt (GMHES) model, designed for electricity price forecasting. Key features of the proposed WOA-GMHES(1,N) model include leveraging historical data to comprehend the underlying trends in electricity prices and utilizing the WOA algorithm for adaptive optimization of model parameters to capture evolving market dynamics. Evaluating the model on authentic high- and low-voltage electricity price data from Cameroon demonstrates its superiority over competing models. The WOA-GMHES(1,N) model achieves remarkable performance with RMSE and SMAPE scores of 12.63 and 0.01 %, respectively, showcasing its accuracy and reliability. Notably, the model proves to be computationally efficient, generating forecasts in <1.3 s. Three key aspects of customization distinguish this novel approach:

• •

  The WOA algorithm dynamically adjusts model parameters based on evolving electricity market dynamics.

• •

  The model employs a sophisticated GMHES approach, considering multiple factors for a comprehensive understanding of price trends.

• •

  The WOA-GMHES(1,N) model stands out for its computational efficiency, providing rapid and precise forecasts, making it a valuable tool for time-sensitive decision-making in the energy sector.

Urban areas have detrimental impacts on the ecosystems. Nevertheless, they still supply many ecosystem services (ES), such as Pollination, in different urban green spaces (UGS). Lawns are among the most degraded UGS due to very high human impact. Still, flowers such as Dandelions (Taraxacum officinalis) live in these spaces. These flowers are considered a suitable habitat for pollinators. In this work, we develop a methodology to map Pollination ES potential in urban lawns using an Unmanned Aerial Vehicle. A detailed protocol was developed using high-resolution images, consisting of orthomosaic creation, flower vectorisation, field validation, and finally, Pollination ES potential mapping using Kernel and Point Density. This method can be applied to urban lawns and grasslands in Spring and Summer.

• •

  A novel method was developed to map pollination potential in lawns.

• •

  Dandelions (Taraxacum officinale) were mapped using UAV high-resolution images.

• •

  The method is helpful to identify areas with pollination potential in urban lawns.

Thermal sensors mounted on drones (unoccupied aircraft systems) are popular and effective tools for monitoring cryptic animal species, although few studies have quantified sampling error of animal counts from thermal images. Using decoys is one effective strategy to quantify bias and count accuracy; however, plastic decoys do not mimic thermal signatures of representative species. Our objective was to produce heat signatures in animal decoys to realistically match thermal images of live animals obtained from a drone-based sensor. We tested commercially available methods to heat plastic decoys of three different size classes, including chemical foot warmers, manually heated water, electric socks, pad, or blanket, and mini and small electric space heaters. We used criteria in two categories, 1) external temperature differences from ambient temperatures (ambient difference) and 2) color bins from a palette in thermal images obtained from a drone near the ground and in the air, to determine if heated decoys adequately matched respective live animals in four body regions. Three methods achieved similar thermal signatures to live animals for three to four body regions in external temperatures and predominantly matched the corresponding yellow color bins in thermal drone images from the ground and in the air. Pigeon decoys were best and most consistently heated with three-foot warmers. Goose and deer decoys were best heated by mini and small space heaters, respectively, in their body cavities, with a heated sock in the head of the goose decoy. The materials and equipment for our best heating methods were relatively inexpensive, commercially available items that provide sustained heat and could be adapted to various shapes and sizes for a wide range of avian and mammalian species. Our heating methods could be used in future studies to quantify bias and validate methodologies for drone surveys of animals with thermal sensors.

• •

  We determined optimal heating methods for plastic animal decoys with inexpensive and commercially available equipment to mimic thermal signatures of live animals.

• •

  Methods could be used to quantify bias and improve thermal surveys of animals with drones in future studies.

The total organic carbon (TOC) concentration of particulate samples is a key parameter to characterize soils and sediments. To demonstrate the applicability and reliability of a modified sample preparation method for the direct measurement of TOC contents in suspended particulate samples, we analyzed five certified reference materials (CRMs) with varying TOC concentrations using a Shimadzu TOC-L CPH analyzer. Measured values were calibrated with a multi-point curve that cover the full range of the expected TOC concentrations and the results were validated using statistical values and measures. The method validation reveals that the measurements are accurate and precise for CRMs from marine and soil contexts, but show a low accuracy for the CRM containing polycyclic aromatic hydrocarbons (PAHs). This demonstrates the applicability and reliability of the modified preparation method for direct TOC determination of suspended particulate samples. Therefore, it is relevant for a broader community, beyond geosciences, and for users employing devices of other manufacturers to analyze TOC in suspended particulate samples.

• •

  Modified preparation method uses reduced sample weights and yields accurate and precise results.

• •

  Cost-efficient and environmentally friendly alternative: reduces waste by saving acid and ultrapure water.

• •

  Avoids incomplete dissolution of dolomite by heating acidified samples.