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This book includes a survey of all RFID fundamentals and practices in the first part of the book while the second part focuses on UHF passive technology. This coverage of UHF technology and its components including tags, readers, and antennas is essential to commercial implementation in supply chain logistics and security. Readers of this book should have an electrical engineering background, but have not yet dealt with RFID. To this end, the author is very careful to illustrate all concepts and detail his explanations meticulously. In this way, he will bring the reader along organically showing him/her what to expect, develop, and use while implementing an RFID system.

Cultivated blueberries ( spp.) (Ericaceae) are among the top three exported agricultural commodities of Mexico. Since their commercial debut in 1995, the area of cultivation has increased annually, reflecting the economic importance of this crop. Because species of the moth family Tortricidae associated with blueberries elsewhere are of considerable economic importance, we investigated the tortricid fauna of commercial blueberry plantations in the states of Guanajuato, Jalisco, Michoacan, and Puebla, Mexico. From 2019 to 2021 we collected and reared tortricid larvae and noted the damage they inflicted. We identified six species feeding on leaves, flowers, and/or fruit: (Walsingham) (Walsingham) (Walsingham), (Felder & Rogenhofer), (Razowski & Becker), and (Fernald). The first three are well-known agricultural pests of numerous crops, and are widely distributed throughout southwestern U.S. and northern Mexico; and are polyphagous native species that are encountered uncommonly; and . is a documented Ericaceae-feeder that is widespread in the eastern U.S. For all but , these are the first records of as hosts for these tortricids. We suggest that is important to monitor population levels of these species owing to their potential economic importance, and to expand sampling to other producer states to evaluate their levels of infestation.

This paper studies how people in the Euro Area Member States identified as European during the Great Recession and examines both their perceptions about being European and their attachment to Europe. It analyses the effect of the crisis on the relationship between European and national identifications (the identification approach), including public debt as a key contextual factor. Factors related to the rational instrumental approach and cognitive mobilisation were controlled for. The analyses indicated that the higher a country's public debt, the greater the positive effect that national identification had on the perception of being European, whereas this relationship was negative at lower levels of public debt. Conversely, the higher a country's public debt, the weaker the positive relationship between national identification and the attachment to the EU.

Photo identification is an important tool for estimating abundance and monitoring population trends over time. However, manually matching photographs to known individuals is time-consuming. Motivated by recent developments in image recognition, we hosted a data science challenge on the crowdsourcing platform Kaggle to automate the identification of endangered North Atlantic right whales (Eubalaena glacialis). The winning solution automatically identified individual whales with 87% accuracy with a series of convolutional neural networks to identify the region of interest on an image, rotate, crop, and create standardized photographs of uniform size and orientation and then identify the correct individual whale from these passport-like photographs. Recent advances in deep learning coupled with this fully automated workflow have yielded impressive results and have the potential to revolutionize traditional methods for the collection of data on the abundance and distribution of wild populations. Presenting these results to a broad audience should further bridge the gap between the data science and conservation science communities. La identificación fotográfica es una herramienta importante para la estimación de la abundancia y el monitoreo de las tendencias poblacionales en el tiempo. Sin embargo, corresponder las fotografías con los individuos conocidos requiere de mucho tiempo. Motivados por los avances recientes en el reconocimiento de imágenes, decidimos acoger un reto de datos científicos en la plataforma de colaboración masiva Kaggle para automatizar la identificación de ballenas francas del Atlántico norte (Eubalaena glacialis), especie que se encuentra en peligro de extinción. La solución ganadora identificó automáticamente a las ballenas individuales con una certeza del 87% y con una serie de redes neurales convolucionales para identificar la región de interés en una imagen, rotar, recortar, y crear fotografías estandarizadas de tamaño y orientación uniforme y después identificar al individuo correcto a partir de estas fotografías tamaño pasaporte. Los avances recientes en el aprendizaje profundo acoplados a este flujo de trabajo completamente automatizado han producido resultados impresionantes y tienen el potencial para revolucionar los métodos tradicionales de recolección de datos de abundancia y distribución de las poblaciones silvestres. La presentación de estos resultados ante un público amplio debería reducir aún más el vacío que existe entre los datos científicos y las comunidades científicas para la conservación. 照片识别是评估种群丰度和监测种群动态的重要工具。然而，人工地将照片与已知个体进行比对需耗费 大量时间。受到最近图像识别领域发展的启发我们在众包平台Kaggle网站举办了ー项数据科学挑战，来自动 识到濒危的北太平洋露脊鲸(Eubalaena glad alis)。获胜的方案能以87%的准确率自动识别鲸鱼个体，它利用 一系列卷积神经网络来找到图像上关注的区域，加以旋转、裁剪，并包！建统ー尺寸和方向的标准化照片，然后从 这些类似护照的照片中正确识别出鲸鱼个体。目前深度学习领域的进展加上这种完全自动化的工作流程，已取 得了显著成果，并有可能给野生动物种群丰度和分布的传统数据收集方法带来变革。我们将这些结果呈现给广 大受众以期进ー步缩小数据科学和保护科学群体之间的距离。

The differentiation of Cinchona spp. hybrids genotypes are challenging due to their shared origins and morphological similarities. This study utilized ISSR (Inter Simple Sequence Repeat) markers to distinguish between genotypes of Cinchona spp.: LF40, LC29, LF74, LF74GB, and LF211 maintained in vitro and ex vitro in Colombia. Genomic DNA was extracted from the plant materials, and eight ISSR primers were used for PCR amplification. In total 61 loci were amplified, of which 37 (60.92%) were polymorphic. The total number of loci per primer ranged from 5 to 12, with an average of 7.62, and polymorphic loci varied from 3 to 6, averaging 4.62 per primer. Cluster analysis based on the unweighted pair group method with arithmetic mean (UPGMA) grouped the genotypes into distinct clusters, showing genetic differences. Principal coordinate analysis (PCA) confirmed the clustering patterns, further distinguishing the genotypes despite their shared origins. The primer ISSR4 was the most effective, with the highest polymorphism rate (75%) and PIC value (0.473), followed by ISSR6 which had a polymorphism rate of 71% and a PIC value of 0.426, both primers allowed the identification of a group of plants under field conditions from in vitro cultures, with unknown genotype origin. As a result, it was possible to confirm a cluster of plants belonging to the LF40 genotype using only two primers. The results demonstrate the genetic distinctiveness of the selected Cinchona genotypes and underscore the utility of ISSR markers as a reliable tool for identifying genetic differences of in vitro and ex vitro Cinchona plant selections. La diferenciación de genotipos híbridos de Cinchona spp.  es un desafío debido a sus orígenes compartidos y similitudes morfológicas. En este estudio se utilizaron marcadores ISSR para distinguir entre los genotipos de Cinchona spp.: LF40, LC29, LF74, LF74GB y LF211, mantenidos en condiciones in vitro y ex vitro en Colombia. Se extrajo ADN genómico de los materiales vegetales y se utilizaron ocho cebadores ISSR para la amplificación por PCR. En total, se amplificaron 61 loci, de los cuales 37 (60,92%) fueron polimórficos. El número total de loci por cebafdor varió de 5 a 12, con un promedio de 7,62, y los loci polimórficos variaron de 3 a 6, con un promedio de 4,62 por cebador. El análisis de conglomerados basado en el método de grupos de pares no ponderados con media aritmética (UPGMA) agrupó los genotipos en distintos clusters, mostrando diferencias genéticas. El análisis de coordenadas principales (PCA) confirmó los patrones de agrupamiento, distinguiendo aún más los genotipos a pesar de sus orígenes compartidos. El cebador ISSR4 fue el más efectivo, con la mayor tasa de polimorfismo (75%) y valor PIC (0.473), seguido del ISSR6 que tuvo una tasa de polimorfismo del 71% y un valor PIC de 0.426, ambos cebadores permitieron la identificación de un grupo de plantas en condiciones de campo a partir de cultivos in vitro, con origen genotípico desconocido. Como resultado, fue posible confirmar un grupo de plantas pertenecientes al genotipo LF40 utilizando sólo dos cebadores. Los resultados demuestran la distinción genética de los genotipos de Cinchona seleccionados y subrayan la utilidad de los marcadores ISSR como una herramienta confiable para identificar diferencias genéticas de selecciones de plantas de Cinchona in vitro y ex vitro.

Provides a much-needed update to the mammalogy of Melanesia, Micronesia and Polynesia.

This guide is intended to help all those interested in identifying mosquitoes from this area, including persons without specialized knowledge. Several colour photographs of adult mosquitoes are included, as well as coloured distribution maps for 38 of the 46 species. There are also quick identification notes for adults and larvae of the 35 more common mosquito species.

The rapid rise of citizen science, with lay people forming often extensive biodiversity sensor networks, is seen as a solution to the mismatch between data demand and supply while simultaneously engaging citizens with environmental topics. However, citizen science recording schemes require careful consideration of how to motivate, train, and retain volunteers. We evaluated a novel computing science framework that allowed for the automated generation of feedback to citizen scientists using natural language generation (NLG) technology. We worked with a photo-based citizen science program in which users also volunteer species identification aided by an online key. Feedback is provided after photo (and identification) submission and is aimed to improve volunteer species identification skills and to enhance volunteer experience and retention. To assess the utility of NLG feedback, we conducted two experiments with novices to assess shortterm (single session) and longer-term (5 sessions in 2 months) learning, respectively. Participants identified a specimen in a series of photos. One group received only the correct answer after each identification, and the other group received the correct answer and NLG feedback explaining reasons for misidentification and highlighting key features that facilitate correct identification. We then developed an identification training tool with NLG feedback as part of the citizen science program BeeWatch and analyzed learning by users. Finally, we implemented NLG feedback in the live program and evaluated this by randomly allocating all BeeWatch users to treatment groups that received different types of feedback upon identification submission. After 6 months separate surveys were sent out to assess whether views on the citizen science program and its feedback differed among the groups. Identification accuracy and retention of novices were higher for those who received automated feedback than for those who received only confirmation of the correct identification without explanation. The value of NLG feedback in the live program, captured through questionnaires and evaluation of the online photo-based training tool, likewise showed that the automated generation of informative feedback fostered learning and volunteer engagement and thus paves the way for productive and long-lived citizen science projects. El rápido crecimiento de la ciencia ciudadana, generalmente con personas laicas formando redes extensas de sensores de la biodiversidad, es visto como una solución a la disparidad entre la demanda y el suministro de datos, a la vez que compromete a los ciudadanos con temas ambientales. Sin embargo, los esquemas de registro de la ciencia ciudadana requieren de consideraciones cuidadosas sobre cómo motivar, entrenar y retener a los voluntarios. Evaluamos un novedoso marco de trabajo científico y computacional que permitió la generación automatizada de retroalimentación para los ciudadanos científicos que usan tecnología de generación de lenguaje natural (GLN). Trabajamos con un programa de ciencia ciudadana basado en fotografías en el cual los usuarios también ofrecen identificación de especies con ayuda de una clave en línea. La retroalimentación es proporcionada después de presentar (e identificar) la fotografía y tiene como objetivo el mejoramiento de las habilidades de identificación del los voluntarios y el aumento en la experiencia y retención de voluntarios. Para evaluar la utilidad de la retroalimentación de GLN llevamos a cabo experimentos con novatos para así poder evaluar el aprendizaje a corto (sesión única) y a largo plazo (cinco sesiones en dos meses), respectivamente. Los participantes identificaron especímenes en una serie de fotos. Un grupo recibió solamente la respuesta correcta después de cada identificación, mientras que el otro grupo recibió la respuesta correcta además de la retroalimentación de GLN, la cual explica las razones por las que se identifica erróneamente y resalta los caracteres clave que facilitan la identificación correcta. Después desarrollamos una herramienta para el entrenamiento en la identificación con la retroalimentación de GLN como parte del programa de ciencia ciudadana BeeWatch y analizamos el aprendizaje de los usuarios. Finalmente, implementamos retroalimentación de GLN en el programa en vivo y evaluamos esto al asignar al azar a todos los usuarios de BeeWatch a grupos de tratamiento que recibieron diferentes tipos de retroalimentación al presentar la identificación. Después de seis meses, se enviaron encuestas separadas para evaluar si las opiniones sobre el programa de ciencia ciudadana y su retroalimentación variaban entre los grupos. La certeza en la identificación y la retención de novatos fueron mayores para aquellos grupos que recibieron la retroalimentación automatizada que para aquellos que sólo recibieron la confirmación de la identificación correcta sin la explicación. El valor de la retroalimentación de GLN en el programa en vivo, capturado por medio de cuestionarios y la evaluación en línea de la herramienta de entrenamiento basada en fotos, también mostró que la generación automatizada de retroalimentación informativa promueve el aprendizaje y el compromiso de los voluntarios, lo que sienta el camino para proyectos de ciencia ciudadana productivos y de larga vida.

While conducting taxonomic studies on the tribe Podochileae (Orchidaceae) for the Flora of India, two species, Ceratostylis siamensis and Ceratostylis himalaica have been examined using types, protologues, fresh specimens, and authentic herbarium collections. Ceratostylis siamensis was previously reported and documented in Arunachal Pradesh, India. However, we determined upon closer examination that this record was based on erroneous identification. The correct identity of this species is C. himalaica. Consequently, Ceratostylis siamensis is excluded from the flora of India.

Many mealybug species (Hemiptera: Coccomorpha: Pseudococcidae) are notably invasive and economically significant. They directly harm plants by extracting sap from the phloem, which diminishes plant vigor, induces chlorosis, and causes defoliation. Their excretion of honeydew promotes the growth of black sooty mold, reducing the aesthetic value of plants and obstructing photosynthesis. Additionally, mealybugs serve as vectors for plant viruses and toxins. Conversely, many native mealybug species may not be pests and can provide important resources for other insects. Existing taxonomic keys for mealybug identification are limited and not comprehensive for all species in Florida, United States. This study presents the first definitive identification key for the 79 mealybug species established in landscapes or commonly collected in nurseries in Florida. The key utilizes morphological characters of slide-mounted adult females. Our key will enable researchers, extension agents, identifiers, and regulators to make accurate identifications, which are crucial for comprehending the ecology, economic impact, control strategies, and significance of mealybugs. This, in turn, facilitates timely and effective management and regulatory measures to safeguard the United States agricultural industry.