Original Design Research Articles

Finite Element Analysis and Optimization of PDCPD New Material Wall Formwork

Thermosetting polydicyclopentadiene (PDCPD) is a new material with high performance, which is expected to replace the traditional steel in the application of cast-in-place formwork components in house construction. In this paper, the finite element model is established by Abaqus to simulate and analyze the floor formwork with the largest size and span in the engineering example, so as to verify the feasibility of this component. The results show that the strength of the floor formwork meets the requirements under the vertical pressure of concrete, but its deformation does not meet the requirements. Therefore, the design optimization is carried out on the basis of the original design, and the main longitudinal ribs are reinforced with steel plates along the span direction. The verification results show that the optimization scheme is suitable.

Analysis procedures accounting for load redistribution mechanisms in masonry earth retaining structures under traffic loading

This paper introduces novel analysis procedures for the structural assessment of masonry earth retaining structures subjected to traffic loading. Given their substantial presence, particularly in transportation networks of historical cities, and the challenges posed by ageing, deterioration, and exposure to loads beyond their original design considerations, this research highlights the necessity of accounting for potential load redistribution mechanisms during their assessment. This can prevent overly conservative interventions that may not be necessary and also contravene sustainability and heritage preservation principles. Four distinct analysis procedures – 2D monotonic, 3D monotonic, 3D static moving load and 3D dynamic moving load – are developed, each progressively more refined than its predecessor in capturing potential load redistribution mechanisms in masonry earth retaining structures. These mechanisms may develop due to the dynamic loading conditions of the vehicular passage, the 3D structural configuration of retaining structures, and non-linear material behaviour. By comparing the structural capacity evaluated using the four procedures, contributions from different sources of load redistribution can be separately quantified, aiding in the reduction of conservatism inherent in less refined assessment procedures. The application of the developed procedures and consequent quantification of load redistribution is demonstrated through a case study of an existing masonry retaining structure in Amsterdam, the Netherlands.

Geographically weighted regression model-calibration for finite population parameter estimation under two stage sampling design

In many agricultural, forestry, environmental, and ecological surveys, data are often spatial in nature and exhibit spatial nonstationarity. A well-known method for addressing spatial nonstationarity and capturing the spatially varying relationships between different variables is Geographic Weighted Regression (GWR). The calibration approach is one of the most widely used techniques in sample surveys for incorporating the known population characteristics of auxiliary variables by changing the original sampling design weights. The model-calibration approach is an improvement on the conventional calibration approach that can handle a variety of assisting working models. Two-stage sampling is one of the most frequently used sampling strategies in large-scale sample surveys. In the present study, a couple of GWR model-calibration estimators were proposed under two-stage sampling, assuming the availability of population-level complete auxiliary information. Under a set of regularity assumptions, the asymptotic properties of the developed estimators have been evaluated such as design unbiasedness, model unbiasedness, approximate variance, and estimators of variances. The performance of the developed estimators has been compared with the existing estimators through a spatial simulation study and a design-based simulation based on real data. The performance of the proposed estimator was found to be more precise than the existing estimators under two-stage sampling.

Robust design space of compression parameters for initial and reprocessed granules

The design of experiments has been widely used for product and process development based on Quality by design (QbD) approach to achieve quality product. Sources of variability are identified and controlled during manufacturing. However, uncertainty due to uncontrollable variables in the process leads to quality issues and the need for reprocessing in some cases. This study proposes a systematic approach to determine the robust design space for process parameters embraced with the variation of initial and reprocessed materials to ensure that the tablet will meet the specification. The Taguchi L36 experiment design is applied to determine suitable tableting parameters for different granules to ensure physical specifications. Four types of calcium carbonate granules were produced with different moisture contents (ZM) and manufacturing conditions (ZT). Additionally, three critical parameters of tablet compression process—filling volume (XV), compression force (XF), and turret speed (XS)—each encompassing three levels, were selected as input variables. The responses were derived from the product specification, namely weight (YW), tensile strength (YTS), and disintegration time (YDT). The experiment results were embedded into two models: the single independence response model (SRM) and the multiple dependent response model (MRM). After a confirmation experiment using predicted parameters, a comparison of their %MAPE (mean average percentage error) revealed that MRM has lower accuracy in terms of YTS but dominates SRM in terms of the region of design space. This finding relates to the effect of data transformation capturing non-linear relationships between these factors and responses. The design space derived from the models allows manufacturers to adjust critical process parameters for getting desired specification tablets and also provides a framework for continuous improvement by enhancing their original design space and providing a rigorous reprocessing plan.

Auditory illusions and Post-traumatic stress disorder: Sound test in a case-control study

Post-Traumatic Stress Disorder (PTSD) is a prevalent and disabling disorder with a high degree of comorbidity. Clinical studies have focused on hallucinations, which could be associated with the severity of the disorder and treatment resistance. Auditory illusions have received little attention so far, possibly because they are particularly difficult to assess. However, they may impact functioning, and underdiagnosis could impair prognosis. To provide a clearer understanding of PTSD psychopathology, this paper proposes to focus on these auditory illusions.A monocentric case-control study was conducted on 30 subjects with PTSD and 30 controls, based on an original design. False recognitions were estimated during a sound test created with a vocoder. Additionally, differences in emotional valence, dissociation, hyperarousal, and reliving were assessed.The study found that individuals with PTSD experience a higher frequency of auditory illusions compared to healthy controls (65% versus 20%, p < 0.001). Additionally, the emotional valence of these illusions was more negative in individuals with PTSD than in controls. The study also identified a correlation between dissociation symptoms, hyperarousal and reliving with auditory illusions.These findings are in line with neurobiological studies of PTSD, as well as cognitive predictive models, and support the hypothesis of a significant prevalence of auditory illusions in PTSD. Like hallucinations, auditory illusions may be influenced by dissociation. Although these results are preliminary, they suggest a need for further investigation into auditory illusions in PTSD and their effect on prognosis.

Investigation of the radiated emission of honeycomb structured aluminum foam/cellular heatsinks at 1–10 GHz

Metal foams or cellular structures like honeycombs, can also be evaluated according to mechanical, acoustic, thermal, and chemical resistance parameters in terms of functionality. However, it is vital to investigate the performance of these cellular structures' radiated emission (RE), which can be used as PCB heatsinks. In this study, the radiated emission (RE) performance of honeycomb-structured aluminum foam (or cellular) heatsinks (AFH), which can be considered as unidirectional regular foam, is examined in the frequency range of 1–10 GHz as a novelty. Also, the effect of four primary variables (the geometry of AFH, honeycomb hole direction, honeycomb cell size, and honeycomb cell wall thickness) on the RE performance of AFH is investigated. Unlike classical honeycomb production methods, the investment flask mold casting (loss wax) method is preferred due to the complex offset strip geometry of designed honeycombs. The original design offset hexagonal honeycomb structures were successfully produced using this investment casting method with additive manufacturing technologies from molten metal. While all simulations are carried out using CST Studio Suite, the RE performance of the proposed AFHs is measured in a standard 3 m fully anechoic chamber using a reference horn antenna and vector network analyzer (VNA). When the results are examined, the measured and simulated results agree with each other quietly. Regarding RE, structures with a CPI value of 14 are better at low frequencies, while structures with a CPI value of 3.5 are better at high frequencies. Secondly, the honeycomb cell thickness value does not significantly affect EMI performance. Lastly, although there is no significant difference in EMI in the low-frequency region, it is better to use a directional structure with vertical holes in the high-frequency region. As a result, in the design of AFH, the RE performances of the heatsinks and their thermal performance should be considered.

Design and optimization analysis of pylon open lower corbel

This study, centered around the engineering context of the Wuxue Yangtze River Bridge, addresses the challenge of significant temperature-induced secondary internal forces in the short lower tower column. A novel open lower corbel tower scheme is proposed as a solution. Firstly, comprehensive finite element models are established for both the open lower corbel pylon scheme and the traditional lower continuous beam pylon scheme. These models are employed for finite element analysis to derive bending moments and displacements of the bridge pylon under various loads, including permanent, vehicle, temperature, and wind loads. Subsequently, considering internal force distribution and stiffness, a comparative assessment is made between the open lower corbel cable pylon scheme and the traditional lower continuous beam cable pylon scheme. The findings reveal that the open corbel structure bridge pylon exhibits lower transverse bending moment values under the influence of permanent load, vehicle load, temperature load, and wind load. This reduction is advantageous for mitigating the issue of significant temperature-induced secondary internal forces in the bridge pylon. Additionally, the transverse bridge stiffness of the open lower corbel cable pylon scheme is found to be on par with that of the lower continuous beam cable pylon scheme. Moreover, topology optimization of the original corbel design is accomplished using the relative density method. The computational results demonstrate that the corbel’s stress and deformation under vertical loads meet code requirements. These research findings offer valuable insights for the design and construction of similar projects.

Numerical study on a new manifold ring-shaped microchannel structure for circular heat source with excellent temperature uniformity

The manifold microchannel heat sink shows great potential for cooling high-heat-flux electronic equipment owing to its exceptional thermal and flow performance. A new manifold ring-shaped channel design is introduced to improve the temperature uniformity for circular heat sources. A comparative analysis of the manifold straight channel, radial expansion channel and manifold ring-shaped channel designs is conducted based on the same heating area under equal mass flow conditions by numerical investigation using single-phase de-ionized water. The findings indicate that the newly proposed manifold ring-shaped channel design exhibits a lower maximum temperature, a lower average temperature, a better temperature uniformity and a smaller pressure drop in comparison to the straight channel and radial channel designs. Specifically, at a mass flow rate of 2.5 g/s, the ring-shaped channel design demonstrates a 71.4 % and 45.4 % reduction in the temperature difference between the maximum temperature and the minimum temperature of the heating surface, and the coefficient of performance is enhanced by 458.2 % and 169.7 % when compared to the straight channel and radial channel designs, respectively. Additionally, three improved designs based on the original manifold ring-shaped channel design are proposed to further enhance fluid flow distribution in the ring-shaped channel design. The results reveal that all three manifold ring-shaped channel optimizations further lower the maximum temperature, the average temperature and the temperature difference. Notably, the improved case3 exhibits the best thermal and hydraulic performances among all structures. When compared to straight channel and radial channel designs, the improved case3 demonstrates an 86.9 % and 75.0 % reduction in the temperature difference, and an increase of 201.2 % and 523.4 % in coefficient of performance under the equal mass flow comparison basis. A heat flux of 1200 W/cm2 can be dissipated at 6 g/s when the maximum temperature rise is kept below 60 K, with a pressure drop of 38 kPa.

Assessment of the effect of thermal barrier coating blockage on film cooling effectiveness: An experimental study of full-coverage turbine vane

The improved performance of turbine blades leads to increased temperature loads, thereby necessitating higher design standards for heat protection. Thermal barrier coating (TBCs) and film cooling are the predominant technologies employed for blade cooling. However, the application of thermal barrier coatings through spraying inevitably modifies the structure of film holes, resulting in deviations from the original design in film cooling. In this study, numerical calculations are used to examine the impact of TBCs blockage on coolant mixing and flow mechanisms in the film holes at typical locations on the vane surface. Additionally, models with actual engine vane dimensions were developed, and the full-coverage film cooling effectiveness (.) vanes with and without TBCs were measured using Pressure-sensitive paint (PSP). The results indicate that the impact of TBCs blockage on the cooling characteristics of cylindrical holes is more pronounced than that of laid-back fan-shaped holes. The TBCs blockage leads to a redistribution of coolant, causing a greater tendency for the coolant to flow out from the hole rows on the suction surface in the tested vane. This results in higher η on the suction surface for the vane with TBCs compared to the vane without TBCs, with a maximum increase of approximately 16.7%. For the other regions of the vane, TBCs spraying significantly reduced η at the leading edge of the vane (with a maximum reduction of approximately 52%) and slightly reduced η at the pressure surface for other regions of the vane (with a maximum reduction of approximately 7%). The application of TBCs reduces the uniformity of film coverage on vane surfaces, with a maximum reduction of approximately 22.5%.

An attention-based multi-scale temporal convolutional network for remaining useful life prediction

Remaining Useful Life (RUL) prediction is one of the key technologies in Prognostics and Health Management (PHM). Accurate RUL prediction is crucial for equipment reliability, and equipment sensor data contains information at different scales that can be used for RUL prediction. Current mainstream methods usually extract features from only a single scale, neglecting the information from other scales. Additionally, the attention mechanisms used in these methods do not incorporate multi-dimensional information, which can lead to a loss in prediction performance. To address this issue, this paper proposes an end-to-end framework which utilizes Multi-Scale Temporal Convolutional Network (MSTCN) to extract multi-scale features and introduces Self-Attention (SA) and Global Fusion Attention (GFA) mechanisms to assist MSTCN's work. SA is located at the head of MSTCN, emphasizing the features of those steps that are particularly important, thereby improving the extraction efficiency of MSTCN. GFA is an original design of attention mechanism located at the end of MSTCN that intelligently integrates multi-dimensional attention information, suppressing redundant information in the multi-scale features. To validate the effectiveness of the proposed method, we conduct experiments on the C-MAPSS dataset released by NASA. The results show that our method outperforms other state-of-the-art prediction methods in terms of RUL prediction performance.

ОБОСНОВАНИЕ КОНСТРУКЦИИ КРЫТОГО ГРУЗОВОГО ВАГОНА С УВЕЛИЧЕННЫМ ОБЪЕМОМ ГРУЗОВОГО ПОМЕЩЕНИЯ

The market of covered freight cars, as well as existing designs of this car type of domestic and foreign production is analyzed. Promising trends of making innovative designs of freight cars for the transportation of piece and container goods are found out. The original design of a covered freight car with an increased body space due to the use of the space between trucks is proposed. To reduce the complexity of loading and unloading operations, sliding sections of the side walls and roof are provided in the car design. To confirm the compliance of the proposed design with the requirements of regulatory and technical documents, the car was entered into the dimension, checking for automatic coupling at the junction of a straight line and a curve, passage in the coupling of an s-shaped curve and coupling of a straight line and a curve, and a single car along a circular curve of a small radius, as well as passing without self-decoupling of the hump of the sorting slide, the ramp exit of the train ferry. A safety assessment is carried out with regard to rolling the wheel onto the rail and overturning the car in curves. The car dynamic characteristics are found out by mathematical modeling methods. The assessment of the strength of the body load-bearing structure, lifting mechanisms of the floor sections, sliding sections of the roof and side walls is performed using the finite element method implemented in the environment of a specialized software package. The results obtained as a result of calculations and computer modeling confirmed the operability and safety of the proposed design of a covered freight car with an increased loading space.

A chemometric and sensory study of Spanish Red Wines labelled “Tempranillo Crianza 2010” with Protected Designation of Origin

A chemometric and sensory study was conducted of ten Spanish red wines, all described as “Tempranillo Crianza 2010”, with Protected Designation of Origin (PDO). The analysis considered the following physicochemical parameters: alcohol content, SO2 level, acidity, tannin, antioxidant capacity and colour. In the chemometric study, Principal Component Analysis of the colour, Cluster Analysis, Analysis Of Variance (ANOVA) and the Kruskal-Wallis test showed that the samples corresponding to PDOs #8, #9 and #10 presented the highest number of differences from the rest. In the sensory analysis, Samples #9 and #10 were identified as the most different. From both types of study, we conclude that Samples #8, #9 and #10 present the greatest differences, while the remaining samples were very similar in their chemometric and sensory characteristics.

Thermal management and fin characteristic optimization of an electronic power supply utilizing Taguchi and ANOVA methods

In the rapidly advancing field of electronic power supplies, managing thermal performance is critical. This study focuses on optimizing fin geometries to enhance the thermal management of an amplifier used in car multimedia systems, utilizing Taguchi and ANOVA methods for both thermal and volumetric efficiencies. Analyses were conducted on the impact of five distinct fin parameters—fin gap, fin thickness, separated plate thickness, fin base thickness, and fin height—on the system’s thermal behavior and the fin volume. Computational Fluid Dynamics (CFD) analyses were performed for 24 different configurations. These analyses showed significant potential for improvement in the original design, with optimizations leading to an 8.31% reduction in the amplifier temperature and a 51.91% reduction in the fin volume. The study identifies fin height as the most effective parameter on the amplifier temperature, with an effect rate of 57.26%, while fin base thickness showed the most significant effect on the fin volume, with an effect rate of 66.98%. These findings not only provide a basis for more efficient design but also offer predictive insights through formulated regression equations, thus reducing the dependency on extensive experimental setups.

Bridging the performance gap between passive and autonomous inflow control devices with a hybrid dynamic optimization technique integrating machine learning and global sensitivity analysis

Wells equipped with flow control devices across their completion intervals have become a proven field development option for geologically complex and/or viscous oil reservoirs. Such wells increase oil recovery, reduce water and gas production, minimize the need for well workover operations, and subsequently lower the wells' carbon footprint. The uncontrolled types of inflow control devices include early-generation passive inflow control devices (ICDs) and later-generation autonomous inflow control devices (AICDs). The superior performance of AICDs over ICDs in managing water and gas production, as well as enhancing the overall well and reservoir performance has been demonstrated in multiple research and case studies. This superiority stems from the AICDs’ ability to self-adjust and increase their flow resistance when undesired fluids (i.e., water and/or gas) flow through them. While ICDs lack this self-adjusting feature, they are more affordable and more readily available on the market.This study aims to reduce the performance gap between passive and autonomous inflow control devices by developing a hybrid dynamic optimization technique. This approach integrates a metaheuristic algorithm, machine learning, global sensitivity analysis, and correlation measures to facilitate the optimization problem by identifying the high-impact control variables. Next, the proposed workflow finds the necessary adjustments to the original well completion design by modifying the high-impact control variables during the optimization process. This results in a modified well completion design that is less influenced by the type of inflow control device (passive or autonomous), thereby bridging the performance gap between these two completion types.The study employs a benchmark ‘Egg field’ model, featuring two multilateral wells (MLWs) producing under a water flooding recovery mechanism. Two different completion designs, utilizing either ICDs or AICDs, are optimized using standard optimization (SO) and the proposed hybrid dynamic optimization techniques. The standard optimization, which employs a standalone Particle Swarm Optimization (PSO) algorithm, highlights, as expected, the superiority of the AICD-based completion, yielding an approximately 13% increase in the net present value (NPV) over the ICD-based completion. However, when applying the hybrid optimization (HO) technique, this difference is significantly reduced to 3.4%. This indicates the potential for the hybrid optimization technique to make ICD-based completions more competitive and economically favourable compared to their AICD-based counterparts.

Exploring consumption profiles, consumer experience and quality claims of Canary Islands' cider (Spain): A multidimensional analysis

AbstractThe exponential expansion of the global cider market positions it as a viable alternative to traditional choices such as wine and beer. Nevertheless, there exists a paucity of research examining the various factors influencing consumer interest in cider. This article undertakes an analysis of the cider consumption experience, with a specific focus on consumer preferences related to distinct quality attributes, encompassing factors like brand, organic certification, and protected designations of origin (PDO). This analysis also takes into consideration the socio‐demographic profile, frequency of consumption, and willingness to pay (WTP). Our study concentrates on the Canary Islands in Spain, an area where no formal certification system yet exists to differentiate locally produced cider in the market. Our data collection methodology encompassed face‐to‐face surveys administered to a probabilistic sample of 1000 respondents in the Canary Islands. The results demonstrate that consumers who place emphasis on quality attributes such as commercial brands, organic certification, and PDOs, tend to assign value to various cognitive aspects of the product. Conversely, those who do not prioritize these quality attributes tend to emphasize the affective dimension of the product and the specific consumption occasions. Additionally, consumers who accord the highest importance to PDOs exhibit a WTP a premium price. The findings of this study hold valuable implications for policymakers and cider manufacturers, aiding them in identifying opportunities for the promotion of Canary Islands cider, both within the local market and on a global scale. [EconLit Citations: A14 Sociology of Economics, Q00 Agricultural and Natural Resource Economics, Environmental and Ecological Economics: General].

Real time monitoring of carbon dioxide levels in surgical helmet systems worn during hip and knee arthroplasty

BackgroundOrthopaedic surgical helmet systems (SHS) rely on an intrinsic fan to force clean external air over the wearer. Carbon dioxide (CO2) is produced through aerobic metabolism and can potentially accumulate inside the SHS. Levels above 2500 ppm have previously been shown to affect cognitive and practical function. Maximum Health and Safety Executive (HSE) 8-h exposure limit is 5000 ppm. There is a paucity of data on real-world CO2 levels experienced during arthroplasty surgery whilst wearing a SHS. ObjectivesTo determine intra-operative levels of CO2 experienced within SHS. MethodsCO2 levels were continuously recorded during 30 elective arthroplasties, both primary and revision. Data was recorded at 0.5Hz throughout the procedure utilising a Bluetooth CO2 detector, worn inside a surgical helmet worn with a toga gown. Five surgeons contributed real time data to the study. ResultsThe average CO2 level across all procedures was 3006 ppm, with 23 of the cases measured within the surgeons’ helmets having a mean above 2500 ppm, but none having a mean above 5000 ppm. For each procedure, the time spent above 2500 and 5000 ppm was calculated, with the means being 72.6 % and 5.4 % respectively. Minimum fan speed was associated with only a marginally higher mean CO2 value than maximum fan speed. DiscussionThe use of surgical helmet systems for elective orthopaedic surgery, can result in CO2 levels regularly rising to a point which may affect cognitive function. ConclusionFurther research is needed to corroborate these findings however, we recommend that future designs of SHS include active management of exhaust gases, possibly returning to Charnley's original design principles of the body exhaust system.

Updated Gene Prediction of the Cucumber (9930) Genome through Manual Annotation.

Thorough and precise gene structure annotations are essential for maximizing the benefits of genomic data and unveiling valuable genetic insights. The cucumber genome was first released in 2009 and updated in 2019. To increase the accuracy of the predicted gene models, 64 published RNA-seq data and 9 new strand-specific RNA-seq data from multiple tissues were used for manual comparison with the gene models. The updated annotation file (V3.1) contains an increased number (24,145) of predicted genes compared to the previous version (24,317 genes), with a higher BUSCO value of 96.9%. A total of 6231 and 1490 transcripts were adjusted and newly added, respectively, accounting for 31.99% of the overall gene tally. These newly added and adjusted genes were renamed (CsaV3.1_XGXXXXX), while genes remaining unaltered preserved their original designations. A random selection of 21 modified/added genes were validated using RT-PCR analyses. Additionally, tissue-specific patterns of gene expression were examined using the newly obtained transcriptome data with the revised gene prediction model. This improved annotation of the cucumber genome will provide essential and accurate resources for studies in cucumber.

A gas sensor based on free-standing SWCNT film for selective recognition of toxic and flammable gases under thermal cycling protocols

The widespread adoption of e-nose devices based on chemiresistive materials has been hindered by issues related to sensor device complexity and reliability, specifically sensor drift, necessitating frequent recalibration and retraining of pattern recognition models. This study introduces a method for thermocycling a single sensor based on a free-standing network of single-walled carbon nanotubes (SWCNTs) to acquire signal patterns for selective analyte detection. Additionally, it employs a data filtering technique to compensate for the sensor drift. A free-standing SWCNT film, only a few nanometers thick, is thermally cycled via Joule heating between room temperature and 120 °C. Under these conditions, the sensitivity was tested towards NO2, H2S, and acetone vapors (10–25 ppm) in the mixture with dry air. Signal patterns produced through thermocycling were processed using CatBoost and LSTM algorithms. The accuracy of detection reached 90 % in the classification task, and the average root mean squared error of analyte concentration detection in the multioutput regression task was below 4 ppm. By combining original sensor design, thermocycling, signal filtering for drift compensation, and advanced pattern recognition models, this work contributes to overcoming the challenges in multivariate sensing systems, paving the way for practical applications of the more reliable chemiresistive sensors.

Tracing the origin and authenticity of Spanish PDO honey using metagenomics and machine learning

The Protected Designation of Origin (PDO) indication for foods intends to guarantee the conditions of production and the geographical origin of regional products within the European Union. Honey products are widely consumed due to their health-promoting properties and there is a general interest in tracing their authenticity. In this regard, metagenomics sequencing and machine learning (ML) have been proposed as complementary technologies to improve the traceability methods of foods. Therefore, the aim of this study was to analyze the metagenomic profiles of Spanish honeys from three different PDOs (Granada, Tenerife and Villuercas-Ibores), and compare them with non-PDO honeys using ML models (PLS, RF, LOGITBOOST, and NNET). According to the results obtained, non-PDO honeys and Granada PDO showed higher beta diversity values than Tenerife and Villuercas-Ibores PDOs. ML classification of honey products allowed the identification of different microbial biomarkers of the geographical origin of honeys: Lactobacillus kunkeei, Parasaccharibacter apium and Lactobacillus helsingborgensis for PDO honeys and Paenibacillus larvae, Lactobacillus apinorum and Klebsiella pneumoniae for non-PDO honeys. In addition, potential microbial biomarkers of some honey varieties including L. kunkeei for Albaida and Retama del Teide varieties, and P. apium for Tajinaste variety, were identified. ML models were validated on an independent set of samples leading to high accuracy rates (above 90 %). This work demonstrates the potential of ML to differentiate different types of honey using metagenome-based methods, leading to high performance metrics. In addition, ML models discriminate both the geographical origin and variety of products corresponding to different PDOs and non-PDO products. Results here presented may contribute to develop enhanced traceability and authenticity methods that could be applied to a wide range of foods.

Research and Implementation of Pneumatic Amphibious Soft Bionic Robot

To meet the requirements of amphibious exploration, ocean exploration, and military reconnaissance tasks, a pneumatic amphibious soft bionic robot was developed by taking advantage of the structural characteristics, motion forms, and propulsion mechanisms of the sea lion fore-flippers, inchworms, Carangidae tails, and dolphin tails. Using silicone rubber as the main material of the robot, combined with the driving mechanism of the pneumatic soft bionic actuator, and based on the theory of mechanism design, a systematic structural design of the pneumatic amphibious soft bionic robot was carried out from the aspects of flippers, tail, head–neck, and trunk. Then, a numerical simulation algorithm was used to analyze the main executing mechanisms and their coordinated motion performance of the soft bionic robot and to verify the rationality and feasibility of the robot structure design and motion forms. With the use of rapid prototyping technology to complete the construction of the robot prototype body, based on the motion amplitude, frequency, and phase of the bionic prototype, the main execution mechanisms of the robot were controlled through a pneumatic system to carry out experimental testing. The results show that the performance of the robot is consistent with the original design and numerical simulation predictions, and it can achieve certain maneuverability, flexibility, and environmental adaptability. The significance of this work is the development of a pneumatic soft bionic robot suitable for amphibious environments, which provides a new idea for the bionic design and application of pneumatic soft robots.