Bio-inspired design of hard-bodied mobile robots based on arthropod morphologies: a 10 year systematic review and bibliometric analysis.

This research presents a 10-year systematic review based on bibliometric analysis of the bio-inspired design of hard-bodied mobile robot mechatronic systems considering the anatomy of arthropods. These are the most diverse group of animals whose flexible biomechanics and adaptable morphology, thus, it can inspire robot development. Papers were reviewed from two international databases (Scopus and Web of Science) and one platform (Aerospace Research Central), then they were classified according to: Year of publication (January 2013 to April 2023), arthropod group, published journal, conference proceedings, editorial publisher, research teams, robot classification according to the name of arthropod, limb's locomotion support, number of legs/arms, number of legs/body segments, limb's degrees of freedom, mechanical actuation type, modular system, and environment adaptation. During the screening, more than 33 000 works were analyzed. Finally, a total of 174 studies (90 journal-type, 84 conference-type) were selected for in-depth study: Insecta-hexapods (53.8%), Arachnida-octopods (20.7%), Crustacea-decapods (16.1%), and Myriapoda-centipedes and millipedes (9.2%). The study reveals that the most active editorials are the Institute of Electrical and Electronics Engineers Inc., Springer, MDPI, and Elsevier, while the most influential researchers are located in the USA, China, Singapore, and Japan. Most works pertained to spiders, crabs, caterpillars, cockroaches, and centipedes. We conclude that 'arthrobotics' research, which merges arthropods and robotics, is constantly growing and includes a high number of relevant studies with findings that can inspire new methods to design biomechatronic systems.

Experimental study and geometrical method to design bio-inspired robotic kinematic chains of inching-locomotion caterpillars.

Inching-locomotion caterpillars (ILAR) show impressive environmental adaptation, having high dexterity and flexibility. To design robots that mimic these abilities, a novel bioinspired robotic design (BIROD) method is presented. The method is composed by an algorithm for geometrical kinematic analysis (GEKINS) to standardize the proportional dimensions according to the insect's anatomy and obtain the kinematic chains. The approach is experimentally applied to analyze the locomotion and kinematic chain of these specimens:Geometridae-two pair of prolegs (represents 35 000 species) andPlusiinae-three pair of prolegs (represents 400 species). The obtained data indicate that the application of the proposed method permits to locate the attachment mechanisms, joints, links, and to calculate angular displacement, angular average velocity, number of degrees of freedom, and thus the kinematic chain.Geometridaein contrast toPlusiinae, shows a longer walk-stride length, a lower number of single-rotational joints in 2D (3 DOF versus 4 DOF), and a lower number of dual-rotational joints in 3D (6 DOF versus 8 DOF). The application of BIROD and GEKINS provides the forward kinematics for 35 400 ILAR species and are expected to be useful as a preliminary phase for the design of bio-inspired arthropod robots.

Investigación española en disforia de género: una revisión de más de 20 años de literatura biomédica / Spanish research in gender dysphoria: a systematic review of more than 20 years of biomedical literature

OBJETIVO: Realizar un análisis bibliométrico y de contenido de la investigación biomédica española sobre disforia de género basado en una revisión de la literatura. MÉTODO: Se realizó una búsqueda en cinco bases de datos internacionales, cuatro nacionales, y dos plataformas editoriales, con la palabra clave "disforia de género" y términos relacionados. Los resultados se combinaron con España y con el nombre de las ciudades españolas con hospital. Se seleccionaron los artículos generados desde las Unidades de Identidad de Género (UIG). El número de citaciones se evaluó mediante el Science Citation Index (SCI) y Google Scholar. RESULTADO: Un total de 179 trabajos fueron incluidos. La producción presenta un incremento progresivo desde 1998 hasta 2015 y un ligero decremento posterior. El 34,6% están publicados en inglés, el 45,8% están basados en casuística de usuarios atendidos, y la temática más frecuente es la psicología y salud mental (58,1%). Los 75 artículos de revistas incluidas en el SCI han recibido 1.252 citas, y los 152 artículos incluidos en Google Scholar, 3.105 citas. La mayor media de citas SCI por artículo corresponde a los publicados en inglés (22,2), basados en casuística (21,1), ámbito de la neuroimagen (52), y generados desde la UIG de Cataluña (25,7). CONCLUSIONES: La producción científica española sobre disforia de género generada desde las UIG ha tenido un cre-cimiento progresivo, abarca una amplia temática, incluye un elevado número de estudios basados en el análisis de la casuística de la población atendida, y las citaciones recibidas reflejan un impacto en la comunidad científica y un liderazgo internacional en algunas áreas como la neuroimagen

OBJECTIVE: To provide a bibliometric and contents analyses of the Spanish research in the field of gender dysphoria based on a literature review. METHOD: Five international and four national databases, and two platforms were used to retrieve publications using the keyword "gender dysphoria" and related terms. The results were combined with Spain and with the name of the Spanish cities' names with a hospital. The articles published from the Gender Identity Units (GIU) being part of the National Health System were selected. The number of citations was assessed using the Science Citation Index (SCI) and Google Scholar. RESULTS: A total of 179 articles were included. Production shows a progressive increase from 1999 to 2015 and a slight de-crease in the following years. 34.6% were published in English, 45.8% were based on set of cases, and the most frequent topic is psychology and mental health (58.1%). The 75 publications indexed in the SCI had received 1,252 citations, and the 152 found in Google Scholar reached 3,105 citations. The highest SCI average citation per article corresponds to those published in English (22.2), based on set of cases (21.1), in the field of neuroimaging (52), and coming from the Catalonia GIU (25.7). CONCLUSIONS: The Spanish research on gender dysphoria produced from the GIUs has had a progressive growth, covers many topics, includes a high number of studies based on set of cases, and the number of citations reflect an impact on the scientific community and international leadership in some areas such as neuroimaging

Application of Composite Spectrum in Agricultural Machines.

Composite spectrum (CS) is a data-fusion technique that reduces the number of spectra to be analyzed, simplifying the analysis process for machine monitoring and fault detection. In this work, vibration signals from five components of a combine harvester (thresher, chopper, straw walkers, sieve box, and engine) are obtained by placing four accelerometers along the combine-harvester chassis in non-optimal locations. Four individual spectra (one from each accelerometer) and three CS (non-coherent, coherent and poly-coherent spectra) from 18 cases are analyzed. The different cases result from the combination of three working conditions of the components-deactivated (off), balanced (healthy), and unbalanced (faulty)-and two speeds-idle and maximum revolutions per minute (RPM). The results showed that (i) the peaks can be identified in the four individual spectra that correspond to the rotational speeds of the five components in the analysis; (ii) the three formulations of the CS retain the relevant information from the individual spectra, thereby reducing the number of spectra required for monitoring and detecting rotating unbalances within a combine harvester; and, (iii) data noise reduction is observed in coherent and poly-coherent CS with respect to the non-coherent CS and the individual spectra. This study demonstrates that the rotating unbalances of various components within agricultural machines, can be detected with a reduced number of accelerometers located in non-optimal positions, and that it is feasible to simplify the monitoring with CS. Overall, the coherent CS may be the best composite spectra formulation in order to monitor and detect rotating unbalances in agricultural machines.

Spanish research in gender dysphoria: A review of more than 20 years of biomedical literature.

To provide a bibliometric and contents analyses of the Spanish research in the field of gender dysphoria based on a literature review.

An SVM-based classifier for estimating the state of various rotating components in agro-industrial machinery with a vibration signal acquired from a single point on the machine chassis.

The goal of this article is to assess the feasibility of estimating the state of various rotating components in agro-industrial machinery by employing just one vibration signal acquired from a single point on the machine chassis. To do so, a Support Vector Machine (SVM)-based system is employed. Experimental tests evaluated this system by acquiring vibration data from a single point of an agricultural harvester, while varying several of its working conditions. The whole process included two major steps. Initially, the vibration data were preprocessed through twelve feature extraction algorithms, after which the Exhaustive Search method selected the most suitable features. Secondly, the SVM-based system accuracy was evaluated by using Leave-One-Out cross-validation, with the selected features as the input data. The results of this study provide evidence that (i) accurate estimation of the status of various rotating components in agro-industrial machinery is possible by processing the vibration signal acquired from a single point on the machine structure; (ii) the vibration signal can be acquired with a uniaxial accelerometer, the orientation of which does not significantly affect the classification accuracy; and, (iii) when using an SVM classifier, an 85% mean cross-validation accuracy can be reached, which only requires a maximum of seven features as its input, and no significant improvements are noted between the use of either nonlinear or linear kernels.

The influence of tractor-seat height above the ground on lateral vibrations.

Farmers experience whole-body vibrations when they drive tractors. Among the various factors that influence the vibrations to which the driver is exposed are terrain roughness, tractor speed, tire type and pressure, rear axle width, and tractor seat height above the ground. In this paper the influence of tractor seat height above the ground on the lateral vibrations to which the tractor driver is exposed is studied by means of a geometrical and an experimental analysis. Both analyses show that: (i) lateral vibrations experienced by a tractor driver increase linearly with tractor-seat height above the ground; (ii) lateral vibrations to which the tractor driver is exposed can equal or exceed vertical vibrations; (iii) in medium-size tractors, a feasible 30 cm reduction in the height of the tractor seat, which represents only 15% of its current height, will reduce the lateral vibrations by around 20%; and (iv) vertical vibrations are scarcely influenced by tractor-seat height above the ground. The results suggest that manufacturers could increase the comfort of tractors by lowering tractor-seat height above the ground, which will reduce lateral vibrations.

A Kalman filter implementation for precision improvement in low-cost GPS positioning of tractors.

Low-cost GPS receivers provide geodetic positioning information using the NMEA protocol, usually with eight digits for latitude and nine digits for longitude. When these geodetic coordinates are converted into Cartesian coordinates, the positions fit in a quantization grid of some decimeters in size, the dimensions of which vary depending on the point of the terrestrial surface. The aim of this study is to reduce the quantization errors of some low-cost GPS receivers by using a Kalman filter. Kinematic tractor model equations were employed to particularize the filter, which was tuned by applying Monte Carlo techniques to eighteen straight trajectories, to select the covariance matrices that produced the lowest Root Mean Square Error in these trajectories. Filter performance was tested by using straight tractor paths, which were either simulated or real trajectories acquired by a GPS receiver. The results show that the filter can reduce the quantization error in distance by around 43%. Moreover, it reduces the standard deviation of the heading by 75%. Data suggest that the proposed filter can satisfactorily preprocess the low-cost GPS receiver data when used in an assistance guidance GPS system for tractors. It could also be useful to smooth tractor GPS trajectories that are sharpened when the tractor moves over rough terrain.

A simple method to improve autonomous GPS positioning for tractors.

Error is always present in the GPS guidance of a tractor along a desired trajectory. One way to reduce GPS guidance error is by improving the tractor positioning. The most commonly used ways to do this are either by employing more precise GPS receivers and differential corrections or by employing GPS together with some other local positioning systems such as electronic compasses or Inertial Navigation Systems (INS). However, both are complex and expensive solutions. In contrast, this article presents a simple and low cost method to improve tractor positioning when only a GPS receiver is used as the positioning sensor. The method is based on placing the GPS receiver ahead of the tractor, and on applying kinematic laws of tractor movement, or a geometric approximation, to obtain the midpoint position and orientation of the tractor rear axle more precisely. This precision improvement is produced by the fusion of the GPS data with tractor kinematic control laws. Our results reveal that the proposed method effectively reduces the guidance GPS error along a straight trajectory.