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Information and communication technologies enable migrants to maintain bonds with multiple communities. Little is known about the association between migrants’ connections to their country of origin and different integration practices in online and offline communities in the receiving society. We draw on a survey conducted amongst migrants in Iceland (N = 2,139) and conduct three regression analyses to identify determinants of migrants’ use of media and social media from their country of origin. Contrary to other studies, we do not find evidence of reactive transnationalism (i.e., migrants seeking out connections to their places of origin due to dissatisfaction with life in the receiving society) as a response to negative attitudes towards the receiving society. We identify distinct patterns of online and offline integration: Migrants with frequent contact with their countries of origin are less integrated locally in terms of offline activities. However, they are more integrated in digital communities of the receiving society, and use receiving-country media more frequently, thus following a strategy of digital biculturalism.

The tilted-wave interferometer is an interferometrical measurement system for the accurate optical form measurement of optical aspheres and freeform surfaces. Its evaluation procedure comprises a high-dimensional inverse problem to reconstruct the form of the surface under test from measured data. Recent work has used a deep learning hybrid approach to solve the inverse problem successfully in a simulation environment. A quantification of the model uncertainty was incorporated using ensemble techniques. In this paper, we expand the application of the deep learning approach from simulations to measured data and show that it produces results similar to those of a state-of-the-art method in a real-world environment.

Recent reports on insect decline have highlighted the need for long‐term data on insect communities towards identifying their trends and drivers. With the launch of many new insect monitoring schemes to investigate insect communities over large spatial and temporal scales, Malaise traps have become one of the most important tools due to the broad spectrum of species collected and reduced capture bias through passive sampling of insects day and night. However, Malaise traps can vary in size, shape, and colour, and it is unknown how these differences affect biomass, species richness, and composition of trap catch, making it difficult to compare results between studies. We compared five Malaise trap types (three variations of the Townes and two variations of the Bartak Malaise trap) to determine their effects on biomass and species richness as identified by metabarcoding. Insect biomass varied by 20%–55%, not strictly following trap size but varying with trap type. Total species richness was 20%–38% higher in the three Townes trap models compared to the Bartak traps. Bartak traps captured lower richness of highly mobile taxa but increased richness of ground‐dwelling taxa. The white roofed Townes trap captured a higher richness of pollinators. We find that biomass, total richness, and taxa group specific richness are all sensitive to Malaise trap type. Trap type should be carefully considered and aligned to match monitoring and research questions. Additionally, our estimates of trap type effects can be used to adjust results to facilitate comparisons across studies.

This paper proposes three different black-box models for a 10-kVA 7.967 kV–120/240 V distribution transformer that is suitable to narrowband power line communication studies. One is valid in the 3–500 kHz range, while the remaining two are simpler models valid for the CENELEC band (3–148.5 kHz). The models are represented as equivalent circuits derived from the rational approximation of the transformer admittance matrix using either phase- or modal-domain theory. All parameters needed for their implementation in electrical circuit solvers are given. Validation is performed not only in frequency domain, but also in time domain, with the application of voltage signals that excite the 3–500 kHz and 3–148.5 kHz frequency bands uniformly. The models are shown to accurately predict the attenuation and distortion of signals transferred through the transformer for a wide range of load conditions for both downstream and upstream signal transmission. Signal attenuation is shown to be load dependent, frequency dependent, and sensitive to the considered transmission path (downstream or upstream).

A review of the book: Nafisa Yeasmin, Waliul Hasanat, Jan Brzozowski, and Stefan Kirchner, eds. Immigration in the Circumpolar North: Integration and Resilience (London: Routledge, 2021)

Deep neural networks have been successfully applied in many different fields like computational imaging, medical healthcare, signal processing, or autonomous driving. In a proof-of-principle study, we demonstrate that computational optical form measurement can also benefit from deep learning. A data-driven machine learning approach is explored to solve an inverse problem in the accurate measurement of optical surfaces. The approach is developed and tested using virtual measurements with known ground truth., Comment: 11 pages, 8 figures

Uncertainty quantification by ensemble learning is explored in terms of an application from computational optical form measurements. The application requires to solve a large-scale, nonlinear inverse problem. Ensemble learning is used to extend a recently developed deep learning approach for this application in order to provide an uncertainty quantification of its predicted solution to the inverse problem. By systematically inserting out-of-distribution errors as well as noisy data the reliability of the developed uncertainty quantification is explored. Results are encouraging and the proposed application exemplifies the ability of ensemble methods to make trustworthy predictions on high dimensional data in a real-world application., 23 pages, 20 figures

O presente trabalho discute algumas técnicas para análise de dados de medidas repetidas, utilizando modelos univariado, multivariado e misto. Discutem-se também algumas questões sobre o problema, bem como alguns procedimentos para seleção do melhor modelo, quando a abordagem de estimação dos parâmetros do modelo misto é via máxima verossimilhança e máxima verossimilhança restrita. Quanto ao modelo univariado de medidas repetidas, foram realizadas simulações para verificação da acurácia dos testes quando as suposições exigidas são válidas, ou não. Este trabalho também discute e compara os procedimentos GLM e MIXED do SAS®, quando utilizados para análise de dados de medidas repetidas. Some technical aspects of repeated measures analysis, using univariate, multivariate and mixed models are discussed in this dissertation. Some problems and procedures to select the adequate model, when the parameters estimation are effectuated through maximum likelihood and restricted maximum likelihood estimation. As for repeated measures, univariate models simulations were done to verify the accuracy of the tests, both when the assumptions are valid or not. This dissertation also discusses and compares the SAS procedures GLM and MIXED when utilized for repeated measures analysis.

O uso da estrutura da rede elétrica para transmissão de dados, tecnologia conhecida como Power Line Communications (PLC), é uma das soluções de comunicação disponíveis para aplicações de redes inteligentes. Em geral, o sistema PLC deve ser capaz de assegurar a transmissão de dados ao longo das linhas de distribuição de média tensão (MT) e também entre as redes de distribuição de média e de baixa tensão (BT). No entanto, a interface entre essas redes é estabelecida por transformadores de distribuição. Como as relações terminais apresentadas por este equipamento possuem características variáveis com a frequência, ele acaba por modificar os sinais transmitidos. Este trabalho propõe modelos para caracterizar o papel de um transformador de distribuição monofásico de 10 kVA, 7967/240-120 V, no contexto de aplicações PLC. Esse transformador, que é amplamente empregado em redes de distribuição rurais no Brasil, foi representado em ampla faixa de frequências usando a técnica de modelagem caixa preta. Os modelos propostos são válidos para faixas de frequência típicas de aplicações de PLC em banda estreita, de 3 a 500 kHz, e para a faixa do CENELEC (3 a 148,5 kHz). Os modelos foram obtidos tanto no domínio das fases quanto no domínio modal a partir da medição de admitâncias e de relações de transferência de tensão. Em um primeiro momento, as respostas em frequência medidas foram aproximadas por funções racionais através da técnica de ajuste vetorial. Em seguida, foram sintetizados circuitos equivalentes compactos, cuja parametrização é fornecida neste trabalho. A validação dos modelos é realizada por meio de estudos em que são comparados dados de medição e resultados de simulações nos domínios da frequência e do tempo para diferentes condições de carga, considerando a transmissão de sinais nos sentidos MT-BT e BT-MT. Os resultados obtidos indicam que os modelos reproduzem o comportamento do transformador de maneira satisfatória para todas as condições terminais testadas e ambos os domínios. Também, foram identificadas faixas de frequência em que a atenuação do sinal é reduzida, o que pode favorecer a transmissão de sinais PLC através de transformadores de distribuição. The use of the power grid for data transmission, technology known as Power Line Communication (PLC), is one of the communication solutions available for smart grid applications. In general, the PLC system must be capable of ensuring data transmission along medium voltage distribution lines and between medium-voltage (MV) and low-voltage (LV) distribution networks. However, the interface between these networks is established by distribution transformers. As the terminal relations introduced by this equipment present frequency-dependent characteristics, the transformer eventually modifies the transmitted signals. This work proposes models to characterize the role of a single-phase distribution transformer of 10 kVA, 7967/240-120 V, in the context of PLC applications. This transformer, which is widely used in rural distribution networks in Brazil, was represented in a wide range of frequencies using the black-box modeling technique. The proposed models are valid for typical frequency ranges of narrowband PLC applications, from 3 to 500 kHz, and in the CENELEC band (3 to 148.5 kHz). The models were obtained in both phase and modal domains from the measurement of admittances and voltage transfer ratios. At first, the measured frequency responses were approximated by rational functions using the vector fitting technique. Then, compact equivalent circuits were synthesized, whose parameterization is provided in this work. The validation of the models is performed through studies comparing measured data and simulation results in the frequency and time domains for different load conditions, considering the transmission of signals in the MV-LV and LV-MV directions. The results indicate that the models reproduce the transformer behavior satisfactorily for all tested terminal conditions and both domains. Also, frequency bands have been identified in which the signal attenuation is reduced, which may support the transmission of PLC signals through distribution transformers.

After publishing the auction conditions for the transmission facilities, concessionaires must assess whether the proposed condition is advantageous for them, taking into account various cost factors, directly financial or not. Given the short time for making this decision, it is important that there is a tool to assist them in this process. In this work, we present an optimization methodology for obtaining the optimal routing of transmission lines between two points, taking into account several financial, social and environmental factors. This problem has been discussed in many previous works, but the most significant difference of the proposed methodology is that it is an adaptation of a preeminent technique for the motion planning of robots: (Optimal) Rapid Random Trees, since there is a strong analogy between the problem of optimal routing of transmission lines and that of optimal motion planning of robots. The algorithm is detailed and results for three scenarios with moderate complexity are presented. These results are compatible with the experience of professionals from the field who supervised this research.

The Brazilian power system is mainly composed of hydroelectric generation. Due to the stochasticity of inflows each hydroelectric plant receives an assured energy certificate, also known as physical guarantees. In general, the assured energy certificates correspond to the energy that each plant can produce at a 95% confidence level., They also represent the maximum energy each hydro unit can contract. So, the hydro generators are constrained by the assured energy and they determine their portfolio of energy contracts with free consumers, other generators, distribution companies and trade companies accordingly. The portfolio is composed of bilateral contracts that are, mainly composed of long term contracts negotiated significantly before the power delivery. Even considering that the assured energy is constant, each generator can seasonalize it on a monthly base, but keeping to the total annual assured energy. This paper aims to use stochastic dual dynamic programming to optimize the seasonalization of this assured energy considering the bilateral contracts previously assigned and the projection of the spot price. The results obtained show a considerable increase in the revenues of a generator utility from the Brazilian system.

In this study, we use a stochastic representation of wind for medium/long-term planning problems that are associated with the operation of hydro-thermal systems. The stochastic dual dynamic programming (SDDP) technique is used in this study. Synthetic wind and hydrological scenarios are generated using a periodic autoregressive model (PAR (p)). This algorithm has wide applicability in countries with a predominantly hydroelectric energy matrix that is associated with high penetration of thermal and wind generation, as in the Brazilian power system. The nonlinearities of the hydraulic production function also was been taking into account. The developed technique can be applied due to the global expansion of power generation over the last two decades with the increasing integration of alternative sources.

Em experimentos com medidas repetidas, quando se utiliza o esquema de parcelas subdivididas, o teste F com relação à subparcela, só terá distribuição F exata caso a matriz de covariâncias atenda a condição de esfericidade. O objetivo deste trabalho foi verificar por meio de simulações, a acurácia da análise através da observação de casos em que a matriz de covariâncias atende, ou não, à condição de esfericidade. Quando utilizadas as matrizes de covariâncias do tipo componente de variância e simetria composta, que atendem a condição de esfericidade, a acurácia da análise foi satisfatória. O mesmo não ocorreu com outras estruturas da matriz de covariâncias. Com relação aos efeitos dos parâmetros, dependendo da grandeza dos valores dos efeitos, estes influenciam o resultado dos testes no sentido de superestimar a indicação dos mesmos, isto quando o intervalo de variação é grande.

Em experimentos com medidas repetidas, quando se utiliza o esquema de parcelas subdivididas, o teste F com relação à subparcela, só terá distribuição F exata caso a matriz de covariâncias atenda a condição de esfericidade. O objetivo deste trabalho foi verificar por meio de simulações, a acurácia da análise através da observação de casos em que a matriz de covariâncias atende, ou não, à condição de esfericidade. Quando utilizadas as matrizes de covariâncias do tipo componente de variância e simetria composta, que atendem a condição de esfericidade, a acurácia da análise foi satisfatória. O mesmo não ocorreu com outras estruturas da matriz de covariâncias. Com relação aos efeitos dos parâmetros, dependendo da grandeza dos valores dos efeitos, estes influenciam o resultado dos testes no sentido de superestimar a indicação dos mesmos, isto quando o intervalo de variação é grande. In experiments using repeated measurements, when split plot designs are utilized the F test in relation to the subplot will have an exact F distribution only if the matrix of covariance satisfies the sphericity condition. The objective of this article was to verify throught simulation the accuracy of the analysis throught the observation of some cases when the matrix of covariance satisfies or not the sphericity condition. When the matrix of covariance was of the component type of variance and of compound symmetry, the sphericity condition was satisfied and the accuracy of the analysis adequate. This does not happen with other structures of the covariance matrix. In relation to the effects of parameters, depending on the magnitude of the values of the effects, they will interfere with the results of the tests, over estimating the effects when the amplitude of the effects is large.