Effects of Principals’ Provision of Teaching and Learning Materials on Students’ Perfomance in Mathematics in Kenya Certificate of Secondary Education in Meru County

In the past few years, Mathematics performance among secondary school learners in Meru County has been decreasing. The current study aims to evaluate various administrative strategies used by principals and their effects on learners’ grade attainment in Kenya Certificate of Secondary Educationin Meru County. The study examines ways through which principals support mathematics teachers through trainings, seminars, workshops and how the support is translated into students’ performance. The study adopted ex post facto design to collect data and analyze the information for conclusion. The researcher analyzed KCSE data over the previous 5 years in Meru County, interviewed the principals, and designed questionnaire for Mathematics teachers. A total of 836 Mathematics teachers and 299 principals across the county were targeted.Using stratified and random sampling, only 251 Mathematics teachers and 92 principals were engaged, which accounts for only 30% of the target. The researcher used split half technique to test reliability and instrument piloting to ensure validity of the data. The study concluded that principals provided little support to Mathematics teachers to attend seminars and workshops. However, principals defended this by citing low resource budget allocations and inadequate resources to support teachers’ seminars and workshops. The findings of the current study can be used by education ministry, school administrator, teachers, and other stakeholders during the decision-making.

The neural economics of brain aging

Despite remarkable advances, research into neurodegeneration and Alzheimer Disease (AD) has nonetheless been dominated by inconsistent and conflicting theory. Basic questions regarding how and why the brain changes over time remain unanswered. In this work, we lay novel foundations for a consistent, integrated view of the aging brain. We develop neural economics—the study of the brain’s infrastructure, brain capital. Using mathematical modeling, we create ABC (Aging Brain Capital), a simple linear simultaneous-equation model that unites aspects of neuroscience, economics, and thermodynamics to explain the rise and fall of brain capital, and thus function, over the human lifespan. Solving and simulating this model, we show that in each of us, the resource budget constraints of our finite brains cause brain capital to reach an upper limit. The thermodynamics of our working brains cause persistent pathologies to inevitably accumulate. With time, the brain becomes damaged causing brain capital to depreciate and decline. Using derivative models, we suggest that this endogenous aging process underpins the pathogenesis and spectrum of neurodegenerative disease. We develop amyloid–tau interaction theory, a paradigm that bridges the unnecessary conflict between amyloid- and tau-centered hypotheses of AD. Finally, we discuss profound implications for therapeutic strategy and development.

Towards Dynamic lockdown strategies controlling pandemic spread under healthcare resource budget

COVID-19 is one of the deadliest pandemics in modern human history that has killed nearly a million people and rapidly inundated the healthcare resources around the world. Current lockdown measures to curb infection spread are threatening to bring the world economy to a halt, necessitating dynamic lockdown policies that incorporate the healthcare resource budget of people in a zone. We conceive a dynamic pandemic lockdown strategy that employs reinforcement learning to modulate the zone mobility, while restricting the COVID-19 hospitalizations within its healthcare resource budget. We employ queueing theory to model the inflow and outflow of patients and validate the approach through extensive simulation on real demographic and epidemiological data from the boroughs of New York City. Our experiments demonstrate that this approach can not only adapt to the varying trends in contagion in a region by regulating its own lockdown level, but also manages the overheads associated with time-varying dynamic lockdown policies.

Engineered signal-coupled inducible promoters: measuring the apparent RNA-polymerase resource budget

Inducible promoters are a central regulatory component in synthetic biology, metabolic engineering, and protein production for laboratory and commercial uses. Many of these applications utilize two or more exogenous promoters, imposing a currently unquantifiable metabolic burden on the living system. Here, we engineered a collection of inducible promoters (regulated by LacI-based transcription factors) that maximize the free-state of endogenous RNA polymerase (RNAP). We leveraged this collection of inducible promotors to construct simple two-channel logical controls that enabled us to measure metabolic burden – as it relates to RNAP resource partitioning. The two-channel genetic circuits utilized sets of signal-coupled transcription factors that regulate cognate inducible promoters in a coordinated logical fashion. With this fundamental genetic architecture, we evaluated the performance of each inducible promoter as discrete operations, and as coupled systems to evaluate and quantify the effects of resource partitioning. Obtaining the ability to systematically and accurately measure the apparent RNA-polymerase resource budget will enable researchers to design more robust genetic circuits, with significantly higher fidelity. Moreover, this study presents a workflow that can be used to better understand how living systems adapt RNAP resources, via the complementary pairing of constitutive and regulated promoters that vary in strength.

Density Dependent Resource Budget Model for Alternate Bearing

ABSTRACTAlternate bearing, seen in many types of plants, is the variable yield with a strongly biennial pattern. In this paper, we introduce a new model for alternate bearing behavior. Similar to the well-known Resource Budget Model, our model is based on the balance between photosynthesis (carbon accumulation) and reproduction processes. We consider two novel features with our model, 1) the existence of a finite capacity in the tree’s resource reservoir and 2) the possibility of having low (but non-zero) yield when the tree’s energy level is low. We achieve the former using a density dependent resource accumulation function, and the latter by removing the concept of the well-defined threshold used in the Resource Budget Model. At the level of an individual tree, our model has a stable two-cycle solution, which is suitable to model plants in which the alternate bearing behavior is pronounced. We incorporate environmental stochasticity by adding two uncorrelated noise terms to the parameters of the model associated with the carbon accumulation and reproduction processes. Furthermore, we examine the model’s behavior on a system of two coupled trees with direct coupling. Unlike the coupled Resource Budget Model, for which the only stable solution is the out-of-phase solution, our model with diffusive coupling has stable in-phase period-2 solutions. This suggests that our model might serve to explain spatial synchrony on a larger scale.

Resource budget for workface planning in industrial-construction

Purpose The purpose of this paper is to develop a novel analytical approach for workface planning practice in industrial-construction sector such that the construction work package (CWP) resource budget can be sufficiently planned for delivering possible field installation work package (FIWP) schedules with work uncertainty. Design/methodology/approach The relationship between CWP resource budget and FIWP schedules is first elucidated based on workface planning practice. The literature of work packaging, workface planning and project scheduling is reviewed. A novel analytical approach is then developed to quantify CWP resource budget based on a probability theory, in consideration of the probability of occurrence of feasible FIWP schedules formulated based on a resource scheduling approach. The results of case studies given by the new approach are cross validated by using simulation and optimization techniques. Findings The new analytical approach can assist workface planning by quantifying the expected CWP resource budget to deliver the FIWP work scope with certain activities that are planned at project level and with uncertain activities that are found at workface level. Practical implications The new analytical approach helps project and workface planners to reliably deploy CWP resource budget for delivering FIWP schedules instead of guessing the budget based on experience. An industrial-construction project for upgrading oil-sands refinery facility is used to show the practical implications. Originality/value This research develops a new analytical approach for workface planning practice to determine sufficient CWP resource budget for delivering feasible FIWP schedules with work uncertainty.