10,327 research outputs found
Offering behavioral assistance to Latino students demonstrating challenging behaviors
Challenging behaviors can significantly alter the learning environment of any classroom.
Traditionally, schools have implemented practices that remove the offending student
from the classroom, deliver punitive disciplinary actions, or refer the student to special
education evaluation. Unfortunately, such practices have demonstrated little longitudinal
effectiveness, with detrimental outcomes for the referred student, particularly students
from Latino backgrounds. With enrollment projections indicating Latinos will become
the majority in U.S. schools, educators are presented with the opportunity to shift away
from past practices and implement evidence-based practices that concurrently assist
students while addressing challenging behaviors. In this paper, the authors discuss past
disciplinary practices, the adverse effects on Latino students, and offer recommendations
on implementing functional behavioral assessment as a means to better meet the needs of Latino students demonstrating challenging behaviors.peer-reviewe
Strong coprimality and strong irreducibility of Alexander polynomials
A polynomial f(t) with rational coefficients is strongly irreducible if
f(t^k) is irreducible for all positive integers k. Likewise, two polynomials f
and g are strongly coprime if f(t^k) and g(t^l) are relatively prime for all
positive integers k and l. We provide some sufficient conditions for strong
irreducibility and prove that the Alexander polynomials of twist knots are
pairwise strongly coprime and that most of them are strongly irreducible. We
apply these results to describe the structure of the subgroup of the rational
knot concordance group generated by the twist knots and to provide an explicit
set of knots which represent linearly independent elements deep in the solvable
filtration of the knot concordance group.Comment: 16 pages, 6 figure
Prospects for computational steering of evolutionary computation
Currently, evolutionary computation (EC) typically takes place in batch mode: algorithms are run autonomously, with the user providing little or no intervention or guidance. Although it is rarely possible to specify in advance, on the basis of EC theory, the optimal evolutionary algorithm for a particular problem, it seems likely that experienced EC practitioners possess considerable tacit knowledge of how evolutionary algorithms work. In situations such as this, computational steering (ongoing, informed user intervention in the execution of an otherwise autonomous computational process) has been profitably exploited to improve performance and generate insights into computational processes. In this short paper, prospects for the computational steering of evolutionary computation are assessed, and a prototype example of computational steering applied to a coevolutionary algorithm is presented
Youth opportunity spaces in low-emission dairy development in Kenya: Research findings and policy recommendations
The dairy sector in Kenya produces over 4 billion liters of milk per year and supports 1.3 million producer households with a vital contribution to incomes and nutrition. However, total national production fails to meet demand. There is a need for increased efforts to support value chain development growth in the sector. In addition to the potential of dairy to support economic growth, the dairy sector is receiving substantial attention as a pathway to achieve Kenya’s Nationally Determined Contributions (NDCs), commitments to international agreements to reduce greenhouse gas (GHG) emission intensities. Intensification of production would reduce emission intensities by generating a higher volume of milk per unit of GHG emission. However, Kenya’s NDCs
specify that the environmental target of GHG emissions reduction should be pursued in accordance with its broader sustainable development agenda. Low-emission development has significant implications for reaching International Sustainable Development Goals; specifically, Decent Work and Economic Growth (SDG #8) and Gender Equality (SDG #5)
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Fe-Ni Sulphides within a CM1 clast in Tagish Lake
The composition, abundance and mineral associations of Fe-Ni sulphides within a CM1 clast in Tagish Lake are described, and compared with Fe-Ni sulphides in the carbonate-rich and carbonate-poor lithology of Tagish Lake, as well as Fe-Ni sulphides from CI and CM chondrites
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