The BioHealth Capital Region (Maryland, Virginia, and Washington, DC; BHCR) is flush with colleges and universities training students in science, technology, engineering, and mathematics disciplines and has one of the most highly educated workforces in the United States. However, current educational approaches and business recruitment tactics are not drawing sufficient talent to sustain the bioscience workforce pipeline. Surveys conducted by the Mid-Atlantic Biology Research and Career Network identified a disconnect between stakeholders who are key to educating, training, and hiring college and university graduates, resulting in several impediments to workforce development in the BHCR: 1) students are underinformed or unaware of bioscience opportunities before entering college and remain so at graduation; 2) students are not job ready at the time of graduation; 3) students are mentored to pursue education beyond what is needed and are therefore overqualified (by degree) for most of the available jobs in the region; 4) undergraduate programs generally lack any focus on workforce development; and 5) few industry–academic partnerships with undergraduate institutions exist in the region. The reality is that these issues are neither surprising nor restricted to the BHCR. Recommendations are presented to facilitate improvement in the preparation of graduates for today’s bioscience industries throughout the United States.

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Air pollutant data are compositional in character because they describe quantitatively the parts of a whole (atmospheric composition). However, it is common to use air pollutant concentrations in statistical models without considering this characteristic of the data and, therefore, without control of common statistical problems, such as spurious correlations and subcompositional incoherence. This paper now proposes a daily multivariate spatio-temporal model with a compositional approach. The air pollution spatio-temporal model is based on a dynamic linear modelling framework with Bayesian inference. The novel modelling methodology was applied in an urban area for carbon monoxide (CO, mg·m −3 ), sulfur dioxide (SO 2 , μg·m −3 ), ozone (O 3 , μg·m −3 ), nitrogen dioxide (NO 2 , μg·m −3 ), and particulate matter less than 2.5 μm in aerodynamic diameter (PM 2.5 , μg·m −3 ). The proposal complemented and improved the conventional approach in air pollution modelling. The main improvements come from a fast multivariate data description, high spatial-correlation, and adequate modelling of air pollutants with high variability.

Technology and Innovation) implemented an affirmative action policy called "Política de Cuotas" (Quota Policy), in order to fulfill the "Ley Orgánica de Educación Superior" (Organic Law of Higher Education), which states that "Instituciones de Educación Superior (IES)" (Institutions of Higher Education) must implement mandatory policies in favor of historically discriminated and vulnerable groups. Students from these groups, who are characterized by low academic performance, have high rates of academic loss and dropout, which makes this policy inefficient, generating socioeconomic losses to the State, the Institutions, and the population. Because of this, the "Escuela Politécnica Nacional (EPN)", through the "Departamento de Formación Básica (DFB)", implemented a program of academic accompaniment for these students who belong to vulnerable groups, improving their academic performance index, however this students presented high dropout rate due to the economic problems, lack of time form students, and insufficient pedagogical training of the tutors.

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