Partial Cointegration

This paper proposes a simple procedure to test the hypothesis of no cointegration against both threshold cointegration and an intermediate possibility that we call partial cointegration. Asymptotic theory is devel- oped, the power of the proposed test is analysed through simulations and an empirical example is provided.

The mesoscopic magnetron as an open quantum system

Motivated by the emergence of materials with mean free paths on the order of microns, we propose a novel class of solid state radiation sources based on reimplementing classical vacuum tube designs in semiconductors. Using materials with small effective masses, these devices should be able to access the terahertz range. We analyze the DC and AC operation of the simplest such device, the cylindrical diode magnetron, using effective quantum models. By treating the magnetron as an open quantum system, we show that it continues to operate as a radiation source even if its diameter is only a few tens of magnetic lengths.Comment: 11 pages, 7 figures; submitted to Physical Review Applie

Moments structure of ℓ 1-stochastic volatility models

We consider Taylor's stochastic volatility model (SVM) when the innovations of the hidden log-volatility process have a Laplace distribution (ℓ 1 exponential density), rather than the standard Gaussian distribution (ℓ 2) usually employed. Recently many investigations have employed ℓ 1 metric to allow better modeling of the abrupt changes of regime observed in financial time series. However, the estimation of SVM is known to be difficult because it is a non-linear with an hidden markov process. Moreover, an additional difficulty yielded by the use of ℓ 1 metric is the not differentiability of the likelihood function. An alternative consists in using a generalized or efficient method-of-moments (GMM/EMM) estimation. For this purpose, we derive here the moments and autocovariance function of such ℓ 1-based stochastic volatility model

Automatic synthesis of sorting algorithms by gene expression programming + (geometric) semantic gene expression programming + encouraging phenotype variation with a new semantic operator: semantic conditional crossover

Gene Expression Programming (GEP) is an alternative to Genetic Programming (GP). Given its characteristics compared to GP, we question if GEP should be the standard choice for evolutionary program synthesis, both as base for research and practical application. We raise the question if such a shift could increase the rate of investigation, applicability and the quality of results obtained from evolutionary techniques for code optimization. We present three distinct and unprecedented studies using GEP in an attempt to develop understanding, investigate the potential and forward the branch. Each study has an individual contribution on its own involving GEP. As a whole, the three studies try to investigate di erent aspects that might be critical to answer the questions raised in the previous paragraph. In the rst individual contribution, we investigate GEP's applicability to automatically synthesize sorting algorithms. Performance is compared against GP under similar experimental conditions. GEP is shown to be capable of producing sorting algorithms and outperforms GP in doing so. As a second experiment, we enhanced GEP's evolutionary process with semantic awareness of candidate programs, originating Semantic Gene Expression Programming (SGEP), similarly to how Semantic Genetic Programming (SGP) builds over GP. Geometric semantic concepts are then introduced to SGEP, forming Geometric Semantic Gene Expression Programming (GSGEP). A comparative experiment between GP, GEP, SGP and SGEP is performed using di erent problems and setup combinations. Results were mixed when comparing SGEP and SGP, suggesting performance is signi cantly related to the problem addressed. By out-performing the alternatives in many of the benchmarks, SGEP demonstrates practical potential. The results are analyzed in di erent perspectives, also providing insight on the potential of di erent crossover variations when applied along GP/GEP. GEP' compatibility with innovation developed to work with GP is demonstrated possible without extensive adaptation. Considerations for integration of SGEP are discussed. In the last contribution, a new semantic operator is proposed, SCC, which applies crossover conditionally only when elements are semantically di erent enough, performing mutation otherwise. The strategy attempts to encourage semantic diversity and wider the portion of the semantic-solution space searched. A practical experiment was performed alternating the integration of SCC in the evolutionary process. When using the operator, the quality of obtained solutions alternated between slight improvements and declines. The results don't show a relevant indication of possible advantage from its employment and don't con rm what was expected in the theory. We discuss ways in which further work might investigate this concept and assess if it has practical potential under di erent circumstances. On the other hand, in regards to the basilar questions of this investigation, the process of development and testing of SCC is performed completely on a GEP/SGEP base, suggesting how the latest can be used as the base for future research on evolutionary program synthesis.Programa c~ao Gen etica por Express~oes (GEP) e uma alternativa recente a Programa c~ao Gen etica (GP). Neste estudo observamos o GEP e colocamos a quest~ao se este n~ao deveria ser tratado como primeira escolha quando se trata de sintetiza c~ao autom atica de programas atrav es de m etodos evolutivos. Dadas as caracteristicas do GEP perguntamonos se esta mudan ca de perspectiva poderia aumentar a investiga c~ao, aplicabilidade e qualidade dos resultados obtidos para a optimiza c~ao de c odigo por m etodos evolutivos. Neste estudo apresentamos tr^es contribui c~oes in editas e distintas usando o algoritmo GEP. Cada uma das contribui c~oes apresenta um avan co ou investiga c~ao no campo da GEP. Como um todo, estas contribui c~oes tentam obter cohecimento e informa c~oes para se abordar a quest~ao geral apresentada no p aragrafo anterior. Na primeira contribui c~ao, investiga-mos e testamos o GEP no problema da sintese autom atica de algoritmos de ordena c~ao. Para o melhor do nosso conhecimento, esta e a primeira vez que este problema e abordado com o GEP. A performance e comparada a do GP em condi c~oes semelhantes, de modo a isolar as caracteristicas de cada algoritmo como factor de distin c~ao. As a second experiment, we enhanced GEP's evolutionary process with semantic awareness of candidate programs, originating Semantic Gene Expression Programming (SGEP), similarly to how Semantic Genetic Programming (SGP) builds over GP. Geometric semantic concepts are then introduced to SGEP, forming Geometric Semantic Gene Expression Programming (GSGEP). A comparative experiment between GP, GEP, SGP and SGEP is performed using di erent problems and setup combinations. Results were mixed when comparing SGEP and SGP, suggesting performance is signi cantly related to the problem addressed. By out-performing the alternatives in many of the benchmarks, SGEP demonstrates practical potential. The results are analyzed in di erent perspectives, also providing insight on the potential of di erent crossover variations when applied along GP/GEP. GEP's compatibility with innovation developed to work with GP is demonstrated possible without extensive adaptation. Considerations for integration of SGEP are discussed. Na segunda contribui c~ao, adicionamos ao processo evolutivo do GEP a capacidade de medir o valor sem^antico dos programas que constituem a popula c~ao. A esta variante damos o nome de Programa c~ao Gen etica por Express~oes Sem^antica (SGEP). Esta variante tr as para o GEP as mesmas caracteristicas que a Programa c~ao Gen etica Sem^antica(SGP) trouxe para o GP convencional. Conceitos geom etricos s~ao tamb em apresentados para o SGEP, extendendo assim a variante e criando a Programa c~ao Gen etica por Express~oes Geom etrica Sem^antica (GSGEP). De forma a testar estas novas variantes, efectuamos uma experi^encia onde s~ao comparados o GP, GEP, SGP e SGEP entre diferentes problemas e combina c~oes de operadores de cruzamento. Os resultados mostraram que n~ao houve um algoritmo que se destaca-se em todas as experi^encias, sugerindo que a performance est a signi cativamente relacionada com o problema a ser abordado. De qualquer modo, o SGEP obteve vantagem em bastantes dos benchmarks, dando assim ind cios de pot^encial ter utilidade pr atica. De um modo geral, esta contribui c~ao demonstra que e possivel utilizar tecnologia desenvolvida a pensar em GP no GEP sem grande esfor co na adapta c~ao. No m da contribui c~ao, s~ao discutidas algumas considera c~oes sobre o SGEP. Na terceira contribui c~ao propomos um novo operador, o Cruzamento Sem^antico Condicional (SCC). Este operador, baseado na dist^ancia sem^antica entre dois elementos propostos, decide se os elementos s~ao propostos para cruzamento, ou se um deles e mutato e ambos re-introduzidos na popula c~ao. Esta estrat egia tem como objectivo aumentar a diversidade gen etica na popula c~ao em fases cruciais do processo evolutivo e alargar a por c~ao do espa co sem^antico pesquisado. Para avaliar o pot^encial deste operador, realizamos uma experi^encia pr atica e comparamos processos evolutivos semelhantes onde o uso ou n~ao uso do SCC e o factor de distin c~ao. Os resultados obtidos n~ao demonstraram vantagens no uso do SCC e n~ao con rmam o esperado em teoria. No entanto s~ao discutidas maneiras em que o conceito pode ser reaproveitado para novos testes em que possa ter pot^encial para demonstrar resultados possitivos. Em rela c~ao a quest~ao central da tese, visto este estudo ter sido desenvolvido com base em GEP/SGEP e visto a teoria do SCC ser compativel com GP, e demonstrado que um estudo geral a area da sintese de algoritmos por meios evolutivos, pode ser conduzido com base no GEP

The Role of Cytoplasmic mRNA Cap-Binding Protein Complexes in Trypanosoma brucei and Other Trypanosomatids.

Trypanosomatid protozoa are unusual eukaryotes that are well known for having unusual ways of controlling their gene expression. The lack of a refined mode of transcriptional control in these organisms is compensated by several post-transcriptional control mechanisms, such as control of mRNA turnover and selection of mRNA for translation, that may modulate protein synthesis in response to several environmental conditions found in different hosts. In other eukaryotes, selection of mRNA for translation is mediated by the complex eIF4F, a heterotrimeric protein complex composed by the subunits eIF4E, eIF4G, and eIF4A, where the eIF4E binds to the 5'-cap structure of mature mRNAs. In this review, we present and discuss the characteristics of six trypanosomatid eIF4E homologs and their associated proteins that form multiple eIF4F complexes. The existence of multiple eIF4F complexes in trypanosomatids evokes exquisite mechanisms for differential mRNA recognition for translation

Two levels of meaning elaboration in psychological research

Arocha (2021) discusses the “replication crisis,” arguing for models that allow a greater complexity in the relationship between variables and processes. In this comment, we identify a more fundamental issue: the impossibility of eliminating interpretation issues with operational definitions and increased rigor in the measurements of variables and processes. Interpretation is at the core of (a) human action and (b) scientific endeavor. First, considering Vygotsky, we argue that all higher mental processes are sign mediated, influencing psychological research with humans. Second, that the understanding of research results also involves sign mediation and, therefore, it is nonneutral. We suggest two alternative approaches. There needs to be an increase in research that delivers a detailed description of psychological phenomena. Additionally, it is necessary to increase the elucidation of contextual-embeddedness research. Taking into account the two levels of meaning will underline psychology as a scientific discipline of complex phenomena.info:eu-repo/semantics/publishedVersio

Mental health literacy regarding depression and suicide.

Introduction: Mental health literacy enables individuals to recognize the symptoms associated with mental illness, and thus adjust their behavior to manage and seek help and treatment for mental illness. Aims: The present research aims to study determinants of mental health literacy and whether an association exists between mental health literacy and the understanding of content related to depression and suicide. Methods: In each group, the participants read one leaflet about depression or suicide and answered a questionnaire to assess their understanding. All the participants also filled out a mental health literacy self-report. Results: The results showed higher mental health literacy for women and individuals with a higher education. Mental health literacy predicted the understanding of suicide content, but the same did not apply for depression. Conclusions: Mental health literacy stands as an important factor to be considered in developing campaigns and promotional actions. However, its effect remains contingent on the contents and context. It is crucial to consider this interaction in maximizing the campaigns’ impact on the population.info:eu-repo/semantics/publishedVersio

Key Phrase Extraction of Lightly Filtered Broadcast News

This paper explores the impact of light filtering on automatic key phrase extraction (AKE) applied to Broadcast News (BN). Key phrases are words and expressions that best characterize the content of a document. Key phrases are often used to index the document or as features in further processing. This makes improvements in AKE accuracy particularly important. We hypothesized that filtering out marginally relevant sentences from a document would improve AKE accuracy. Our experiments confirmed this hypothesis. Elimination of as little as 10% of the document sentences lead to a 2% improvement in AKE precision and recall. AKE is built over MAUI toolkit that follows a supervised learning approach. We trained and tested our AKE method on a gold standard made of 8 BN programs containing 110 manually annotated news stories. The experiments were conducted within a Multimedia Monitoring Solution (MMS) system for TV and radio news/programs, running daily, and monitoring 12 TV and 4 radio channels.Comment: In 15th International Conference on Text, Speech and Dialogue (TSD 2012