Evaluating implementation of LEAPS, a youth-led early childhood care and education intervention in rural Pakistan: protocol for a stepped wedge cluster-randomized trial

BACKGROUND: The Sustainable Development Goals (SDGs) highlight the importance of investments in early childhood care and education (ECCE) and youth development. Given Pakistan's large young population, and gender and urban-rural inequalities in access to education, training, and employment, such investments offer opportunities. LEAPS is a youth-led ECCE program that trains female youth, 18-24 years, as Community Youth Leaders (CYLs) to deliver high-quality ECCE for children, 3.5-5.5 years, in rural Sindh, Pakistan. METHODS: We use a stepped wedge cluster-randomized trial to evaluate implementation of LEAPS. Ninety-nine clusters will be randomized to receive the intervention in one of three 7-month steps (33 clusters/step). The primary outcome is children's school readiness (indexed by the total score on the International Development and Early Learning Assessment (IDELA)). Secondary child outcomes are children's IDELA domain scores and executive functions. Data are collected in cross-sectional surveys of 1089 children (11 children/cluster from 99 clusters) aged 4.5-5.5 years at four timepoints (baseline and at the end of each step). Additionally, we will enroll three non-randomized youth participant open cohorts, one per step (33 CYLs: 66 comparison youth per cohort; 99:198 in total). Youth cohorts will be assessed at enrollment and every 7 months thereafter to measure secondary outcomes of youth personal and professional development, depressive symptoms, and executive functions. A non-randomized school cohort of 330 LEAPS students (10 students/cluster from 33 clusters) will also be enrolled and assessed during Step 1 after intervention rollout and at endline. The quality of the learning environment will be assessed in each LEAPS ECCE center and in a comparison center at two timepoints midway following rollout and at endline. A concurrent mixed-methods implementation evaluation will assess program fidelity and quality, and the extent to which a technical support strategy is successful in strengthening systems for program expansion. A cost evaluation will assess cost per beneficiary. Data collection for implementation and cost evaluations will occur in Step 3. DISCUSSION: Youth-led models for ECCE offer a promising approach to support young children and youth. This study will contribute to the evidence as a means to promote sustainable human development across multiple SDG targets. TRIAL REGISTRATION: ClinicalTrials.gov NCT03764436 . Registered on December 5, 2018

Remaining idle time aware intelligent channel bonding schemes for cognitive radio sensor networks

Channel bonding (CB) is a technique used to provide larger bandwidth to users. It has been applied to various networks such as wireless local area networks, wireless sensor networks, cognitive radio networks, and cognitive radio sensor networks (CRSNs). The implementation of CB in CRSNs needs special attention as primary radio (PR) nodes traffic must be protected from any harmful interference by cognitive radio (CR) sensor nodes. On the other hand, CR sensor nodes need to communicate without interruption to meet their data rate requirements and conserve energy. If CR nodes perform frequent channel switching due to PR traffic then it will be difficult to meet their quality of service and data rate requirements. So, CR nodes need to select those channels which are stable. By stable, we mean those channels which having less PR activity or long remaining idle time and cause less harmful interference to PR nodes. In this paper, we propose two approaches remaining idle time aware intelligent channel bonding (RITCB) and remaining idle time aware intelligent channel bonding with interference prevention (RITCB-IP) for cognitive radio sensor networks which select stable channels for CB which have longest remaining idle time. We compare our approaches with four schemes such as primary radio user activity aware channel bonding scheme, sample width algorithm, cognitive radio network over white spaces and AGILE. Simulation results show that our proposed approaches RITCB and RITCB-IP decrease harmful interference and increases the life time of cognitive radio sensor nodes

Laser ablation assisted micropattern screen printed transduction electrodes for sensing applications.

In this work we present a facile method for the fabrication of several capacitive transduction electrodes for sensing applications. To prepare the electrodes, line widths up to 300 [Formula: see text]m were produced on polymethyl methacrylate (PMMA) substrate using a common workshop laser engraving machine. The geometries prepared with the laser ablation process were characterised by optical microscopy for consistency and accuracy. Later, the geometries were coated with functional polymer porous cellulose decorated sensing layer for humidity sensing. The resulting sensors were tested at various relative humidity (RH) levels. In general, good sensing response was produced by the sensors with sensitivities ranging from 0.13 to 2.37 pF/%RH. In ambient conditions the response time of 10 s was noticed for all the fabricated sensors. Moreover, experimental results show that the sensitivity of the fabricated sensors depends highly on the geometry and by changing the electrode geometry sensitivity increases up to 5 times can be achieved with the same sensing layer. The simplicity of the fabrication process and higher sensitivity resulting from the electrode designs is expected to enable the application of the proposed electrodes not only in air quality sensors but also in many other areas such as touch or tactile sensors.Published onlin

Parenting interventions to promote early child development in the first three years of life: A global systematic review and meta-analysis.

BackgroundParents are the primary caregivers of young children. Responsive parent-child relationships and parental support for learning during the earliest years of life are crucial for promoting early child development (ECD). We conducted a global systematic review and meta-analysis to evaluate the effectiveness of parenting interventions on ECD and parenting outcomes.Methods and findingsWe searched MEDLINE, Embase, PsycINFO, CINAHL, Web of Science, and Global Health Library for peer-reviewed, published articles from database inception until November 15, 2020. We included randomized controlled trials (RCTs) of parenting interventions delivered during the first 3 years of life that evaluated at least 1 ECD outcome. At least 2 reviewers independently screened, extracted data, and assessed study quality from eligible studies. ECD outcomes included cognitive, language, motor, and socioemotional development, behavior problems, and attachment. Parenting outcomes included parenting knowledge, parenting practices, parent-child interactions, and parental depressive symptoms. We calculated intervention effect sizes as the standardized mean difference (SMD) and estimated pooled effect sizes for each outcome separately using robust variance estimation meta-analytic approaches. We used random-effects meta-regression models to assess potential effect modification by country-income level, child age, intervention content, duration, delivery, setting, and study quality. This review was registered with PROSPERO (CRD42018092458 and CRD42018092461). Of the 11,920 articles identified, we included 111 articles representing 102 unique RCTs. Pooled effect sizes indicated positive benefits of parenting interventions on child cognitive development (SMD = 0.32, 95% CI [confidence interval]: 0.23, 0.40, P ConclusionsParenting interventions for children during the first 3 years of life are effective for improving ECD outcomes and enhancing parenting outcomes across low-, middle-, and high-income countries. Increasing implementation of effective and high-quality parenting interventions is needed globally and at scale in order to support parents and enable young children to achieve their full developmental potential

Impact of Injection Protocol Selection by Retina Specialists on Clinical Outcomes in Patients with Diabetic Macular Edema

Intravitreal anti-VEGF injections are the current gold standard for treating diabetic macular edema (DME). However, injection practice patterns of retina specialists have varied markedly based on physician discretion. This retrospective study analyzes the impact of injection protocol selection on change in best-corrected visual acuity (BCVA) and central macular thickness (CMT) in 170 eyes treated by 4 retina specialists practicing a pro re nata (PRN) strategy between 2010 and 2020. DME patients received an average of 7.25 injections every 6.24 weeks over 56.6 weeks. There were significant differences between retina specialists in mean number of injections (p = 0.0001) and mean length of treatment (p = 0.0007) but not in mean interval between injections. Over the treatment period, average change in BCVA was −0.053 logMAR, and average change in CMT was −51.1 µm, neither of which had significant differences between retina specialists. BCVA and CMT at initial visit were found to be significantly associated with improved BCVA and CMT over the treatment period (p < 0.001). Number of injections administered and interval between injections were not found to be significant factors affecting change in BCVA or CMT. Despite significant differences in injection dosing regimen, retina specialists achieved similar outcomes in change in BCVA and CMT over the treatment period

Economic Impact of an Optimization-Based SCADA Model for an Office Building

The daily increment of electricity usage has led many efforts on the network operators to reduce the consumption in the demand side. The use of renewable energy resources in smart grid concepts became an irrefutable fact around the world. Therefore, real case studies should be developed to validate the business models performance before the massive production. This paper surveys the economic impact of an optimization-based Supervisory Control And Data Acquisition model for an office building by taking advantages of renewable resources for optimally managing the energy consumption. An optimization algorithm is developed for this model to minimize the electricity bill of the building considering day-ahead hourly market prices. In the case study, the proposed system is employed for demonstrating electricity cost reduction by using optimization capabilities based on user preferences and comfort level. The results proved by the performance of the system, which leads to having great economic benefits in the annual electricity cost.The present work was done and funded in the scope of the project UID/EEA/00760/2013 funded by FEDER Funds through COMPETE program and by National Funds through FCT.info:eu-repo/semantics/publishedVersio