Blended Whiteboard Enhancement Activities as an Innovation to Improve Learners' Operational Problem Skills in Integers

This study evaluated the learners' operational skills in integers in terms of addition, subtraction, multiplication, division, and positive and negative numbers, as well as their attitude toward integers after using a blended whiteboard activity enhancement application. The study used a one-group pretest-posttest research design to see if the blended whiteboard enhancement activities helped improve learners' operational problem skills. It was done with grade 7 students for their improvement in operational skills including operational integers. The Department of Education's Curriculum Guide required the use of a table of specifications (TOS) to ensure its reliability and validity. The findings revealed that the learners showed closely towards excellent as exposed to blended whiteboard activities enhance positive effect on operational skills on the learners the significantly higher mean in the posttest compared to the pretest indicates that the blended whiteboard activity enhancement application strategy was effective in teaching operational problem skills in integers. The Department of Education's Curriculum Guide required the use of a table of specifications (TOS) to ensure its reliability and validity. The results revealed that whenever learners were exposed to blended whiteboard activities, they improved their operational skills significantly. The significantly higher mean in the posttest compared to the pretest indicates that the blended whiteboard activity enhancement application strategy was effective in teaching operational problem skills in integers. Finally, the results of this study will benefit Math teachers by providing evidence on the efficiency of employing the Whiteboard enhancement application as an innovation in teaching integers to grade 7 learners

Mapping the quality of life experience in Alfama: a case study in Lisbon, Portugal.

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies.This research maps the urban quality of life (QoL) in Alfama, Lisbon (Portugal) through objective and subjective measures. A survey of 69 respondents and locations of social services were gathered signifying the subjective and objective QoL respectively in the physical, economic, and social domain. The relationship between the two measures is examined using correlation analysis. It was determined that the association between them is weak and not significant, which could have been caused by the geographic scale and the sample size chosen. These two factors also affected the spatial autocorrelation check implemented to the 15 subjective indicators using the Moran’s I test. The results of this spatial autocorrelation check were the basis of the type of spatial prediction method used for each indicator. Out of 15, only 3 indicators were spatially autocorrelated. These 3 indicators were interpolated using Ordinary Kriging (OK). The rest is interpolated using the voronoi polygon. The 15 prediction maps were used to create the overall subjective QoL with the utilization of the Multi-Criteria Decision Analysis (MCDA) method called Weighted Sum. With all indicators grouped together, four maps are produced namely, physical, social, economic, and the overall QoL. Both physical and economic domains showed comparatively a below average QoL while the social domain with an average to above average result. The overall, which is the weighted sum of these three domains, generated a below average to an average assessment

Human Papillomavirus (HPV) Vaccination Status Among University Freshmen in Hawai‘i

Purpose/Background: The HPV vaccine provides immunity against nine HPV strains that cause cancer and genital warts. It is recommended for 11 to 12 year olds, and catch-up immunization is recommended for females 13 to 26 years old and males 13 to 21 years old. College students represent an important population for HPV vaccination due to their increased risk for HPV infection. Despite the benefits of the HPV vaccine, its coverage rates are low in Hawaii. Hawai‘i is the home of two large universities on two islands that are representative of Hawai‘i’s populations, including Native Hawaiians, Filipinos, and Pacific Islanders. The purpose of this study was to assess the current HPV and HPV vaccine knowledge, barriers and beliefs among incoming Freshmen university students at University of Hawai‘i at Mānoa and University of Hawai‘i at Hilo. Materials & Methods: In 2016, 200 University of Hawai‘i at Mānoa (UHM) and University of Hawai‘i at Hilo (UHH) Freshmen students responded to a survey that assessed their knowledge and awareness of HPV, the HPV vaccine, their current vaccination status, and barriers and motivators to vaccination. Descriptive statistics were used to summarize each survey variable first for all students and then separately for each campus. Results: Overall 76% of Freshmen from both campuses heard of the HPV vaccine and 54% reported hearing it from their health care provider. Only 28% UHM and 23% UHH Freshmen students have received partial (1-2 shots) or completed doses of the HPV vaccine. For those who received the vaccine, 45% reported that they were told by their parent and 43% were told by their doctor. For the 147 students who did not receive the vaccine, 28% reported that they are still not sure to get it and 20% need more information. Their main reasons for not receiving the HPV vaccine were: their doctor did not mention the vaccine to him/her (44%), he/she never knew about the vaccine (18%), and they don\u27t know enough about the vaccine (17%). Discussion/Conclusion: Although the HPV vaccine has been available for 13 years, young adults remain unvaccinated. Freshmen students reported that they are informed about the vaccine, but were not vaccinated because of the lack of parental and/or healthcare provider recommendation. With no active education campaigns in Hawaii promoting the HPV vaccine at college campuses, a first step to increasing vaccination rates is to develop a health education campaign to inform students of the HPV vaccine and its availability at campus clinics and neighboring pharmacies

Revitalizing Pre-service Teacher Pedagogical Competence and Approaches in Teaching Mathematical Comprehension

his study assessed the preservice teacher's pedagogical competence and approach to teaching mathematical comprehension to the fourth-year learners was evaluated in this study. The research estimates the preservice teacher's level of pedagogical competence in terms of communication, adaptability, collaboration, inclusivity, and compassion and the level of pedagogical approaches in terms of constructivist, collaborative, integrative, reflective, and inquiry-based as well as improving the preservice teacher's knowledge input Enhancement training program as an invention. The study employed a descriptive-correlational research design to test the viability of the preservice teacher pedagogical competence and approaches in teaching mathematical competence that the fourth-year learners will utilize for their improvement in teaching mathematics findings revealed that the preservice teachers showed high competence as exposure to input enhancement training programs had a positive effect on teaching mathematics. The significant relationship between the preservice teacher's pedagogical competence and approaches is moderately positively correlated in teaching mathematical comprehension. Additionally, the findings of this study will benefit the preservice teachers to enhance their knowledge in teaching mathematics by providing them with attending the Proposed Enhancement Program entitled Reimagining the Current Pedagogical Trends in Teaching Mathematical Word Problems to the fourth-year learners

Search for strongly interacting massive particles generating trackless jets in proton–proton collisions ats=13 TeV\sqrt{s} = 13\,\text {TeV}

A search for dark matter in the form of strongly interacting massive particles (SIMPs) using the CMS detector at the LHC is presented. The SIMPs would be produced in pairs that manifest themselves as pairs of jets without tracks. The energy fraction of jets carried by charged particles is used as a key discriminator to suppress efficiently the large multijet background, and the remaining background is estimated directly from data. The search is performed using proton–proton collision data corresponding to an integrated luminosity of 16.1fb$^{-1}$, collected with the CMS detector in 2016. No significant excess of events is observed above the expected background. For the simplified dark matter model under consideration, SIMPs with masses up to 100GeV are excluded and further sensitivity is explored towards higher masses

Measurement of single-diffractive dijet production in proton–proton collisions at s=8 TeV\sqrt{s} = 8\,\text {Te}\text {V} with the CMS and TOTEM experiments

Measurements are presented of the single-diffractive dijet cross section and the diffractive cross section as a function of the proton fractional momentum loss ξ ξ and the four-momentum transfer squared t. Both processes p p → p X p p → p X and p p → X p p p → X p , i.e. with the proton scattering to either side of the interaction point, are measured, where X X includes at least two jets; the results of the two processes are averaged. The analyses are based on data collected simultaneously with the CMS and TOTEM detectors at the LHC in proton–proton collisions at s √ =8TeV s=8TeV during a dedicated run with β ∗ =90m β∗=90m at low instantaneous luminosity and correspond to an integrated luminosity of 37.5nb −1 37.5nb−1 . The single-diffractive dijet cross section σ p X jj σjj p X , in the kinematic region ξ<0.1 ξ<0.1 , 0.03<|t|<1GeV 2 0.03<|t|<1GeV2 , with at least two jets with transverse momentum p T >40GeV pT>40GeV , and pseudorapidity |η|<4.4 |η|<4.4 , is 21.7±0.9(stat) +3.0 −3.3 (syst)±0.9(lumi)nb 21.7±0.9(stat)−3.3+3.0(syst)±0.9(lumi)nb . The ratio of the single-diffractive to inclusive dijet yields, normalised per unit of ξ ξ , is presented as a function of x, the longitudinal momentum fraction of the proton carried by the struck parton. The ratio in the kinematic region defined above, for x values in the range −2.9≤log 10 x≤−1.6 −2.9≤log10⁡x≤−1.6 , is R=(σ p X jj /Δξ)/σ jj =0.025±0.001(stat)±0.003(syst) R=(σjj p X /Δξ)/σjj=0.025±0.001(stat)±0.003(syst) , where σ p X jj σjj p X and σ jj σjj are the single-diffractive and inclusive dijet cross sections, respectively. The results are compared with predictions from models of diffractive and nondiffractive interactions. Monte Carlo predictions based on the HERA diffractive parton distribution functions agree well with the data when corrected for the effect of soft rescattering between the spectator partons

A Deep Neural Network for Simultaneous Estimation of b Jet Energy and Resolution

We describe a method to obtain point and dispersion estimates for the energies of jets arising from b quarks produced in proton-proton collisions at an energy of s = 13 TeV at the CERN LHC. The algorithm is trained on a large sample of simulated b jets and validated on data recorded by the CMS detector in 2017 corresponding to an integrated luminosity of 41 fb - 1 . A multivariate regression algorithm based on a deep feed-forward neural network employs jet composition and shape information, and the properties of reconstructed secondary vertices associated with the jet. The results of the algorithm are used to improve the sensitivity of analyses that make use of b jets in the final state, such as the observation of Higgs boson decay to b b ¯

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)