29 research outputs found
Effects of Automated Interventions in Programming Assignments: Evidence from a Field Experiment
A typical problem in MOOCs is the missing opportunity for course conductors
to individually support students in overcoming their problems and
misconceptions. This paper presents the results of automatically intervening on
struggling students during programming exercises and offering peer feedback and
tailored bonus exercises. To improve learning success, we do not want to
abolish instructionally desired trial and error but reduce extensive struggle
and demotivation. Therefore, we developed adaptive automatic just-in-time
interventions to encourage students to ask for help if they require
considerably more than average working time to solve an exercise. Additionally,
we offered students bonus exercises tailored for their individual weaknesses.
The approach was evaluated within a live course with over 5,000 active students
via a survey and metrics gathered alongside. Results show that we can increase
the call outs for help by up to 66% and lower the dwelling time until issuing
action. Learnings from the experiments can further be used to pinpoint course
material to be improved and tailor content to be audience specific.Comment: 10 page
Stability and pKa Modulation of Aminophenoxazinones and Their Disulfide Mimics by Host-Guest Interaction with Cucurbit[7]uril. Direct Applications in Agrochemical Wheat Models
Aqueous solubility and stability often limit the application of aminophenoxazinones and their sulfur mimics as promising agrochemicals in a sustainable agriculture inspired by allelopathy. This paper presents a solution to the problem using host-guest complexation with cucurbiturils (CBn). Computational studies show that CB7 is the most suitably sized homologue due to its strong affinity for guest molecules and its high water solubility. Complex formation has been studied by direct titrations monitored using UV-vis spectroscopy, finding a preferential interaction with protonated aminophenoxazinone species with high binding affinities (CB7 center dot APOH+ , Ka = (1.85 +/- 0.37) x 106 M-1; CB7 center dot DiS-NH3+ , Ka = (3.91 +/- 0.53) x 104 M-1; and DiS-(NH3+)2 , Ka= (1.27 +/- 0.42) x 105M-1). NMR characterization and stability analysis were also performed and revealed an interesting pKa modulation and stabilization by cucurbiturils (2-amino-3H-phenoxazin-3-one (APO), pKa = 2.94 +/- 0.30, and CB7 center dot APO, pKa = 4.12 +/- 0.15; 2,2 '-disulfanediyldianiline (DiS-NH2), pKa = 2.14 +/- 0.09, and CB7 center dot DiS-NH2 , pKa = 3.26 +/- 0.09), thus favoring applications in different kinds of crop soils. Kinetic studies have demonstrated the stability of the CB7 center dot APO complex at different pH media for more than 90 min. An in vitro bioassay with etiolated wheat coleoptiles showed that the bioactivity of APO and DiS-NH2 is enhanced upon complexation
Supramolecular Click Chemistry for Surface Modification of Quantum Dots Mediated by Cucurbit[7]uril
Cucurbiturils (CBs), barrel-shaped macrocyclic molecules, are capable of self-assembling at the surface of nanomaterials in their native state, via their carbonyl-ringed portals. However, the symmetrical two-portal structure typically leads to aggregated nanomaterials. We demonstrate that fluorescent quantum dot (QD) aggregates linked with CBs can be broken-up, retaining CBs adsorbed at their surface, via inclusion of guests in the CB cavity. Simultaneously, the QD surface is modified by a functional tail on the guest, thus the high affinity host-guest binding (logKa > 9) enables a non-covalent, click-like modification of the nanoparticles in aqueous solution. We achieved excellent modification efficiency in several functional QD conjugates as protein labels. Inclusion of weaker-binding guests (logKa = 4-6) enables subsequent displacement with stronger binders, realising modular switchable surface chemistries. Our general "hook-and-eye" approach to host-guest chemistry at nanomaterial interfaces will lead to divergent routes for nano-architectures with rich functionalities for theranostics and photonics in aqueous systems
Supramolecular Click Chemistry for Surface Modification of Quantum Dots Mediated by Cucurbit[7]uril
Cucurbiturils (CBs), barrel-shaped macrocyclic molecules, are capable of self-assembling at the surface of nanomaterials in their native state, via their carbonyl-ringed portals. However, the symmetrical two-portal structure typically leads to aggregated nanomaterials. We demonstrate that fluorescent quantum dot (QD) aggregates linked with CBs can be broken-up, retaining CBs adsorbed at their surface, via inclusion of guests in the CB cavity. Simultaneously, the QD surface is modified by a functional tail on the guest, thus the high affinity host-guest binding (logKa > 9) enables a non-covalent, click-like modification of the nanoparticles in aqueous solution. We achieved excellent modification efficiency in several functional QD conjugates as protein labels. Inclusion of weaker-binding guests (logKa = 4-6) enables subsequent displacement with stronger binders, realising modular switchable surface chemistries. Our general “hook-and-eye” approach to host-guest chemistry at nanomaterial interfaces will lead to divergent routes for nano-architectures with rich functionalities for theranostics and photonics in aqueous systems
Recommended from our members
Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation
SVM-based synthetic fingerprint discrimination algorithm and quantitative optimization strategy.
Synthetic fingerprints are a potential threat to automatic fingerprint identification systems (AFISs). In this paper, we propose an algorithm to discriminate synthetic fingerprints from real ones. First, four typical characteristic factors-the ridge distance features, global gray features, frequency feature and Harris Corner feature-are extracted. Then, a support vector machine (SVM) is used to distinguish synthetic fingerprints from real fingerprints. The experiments demonstrate that this method can achieve a recognition accuracy rate of over 98% for two discrete synthetic fingerprint databases as well as a mixed database. Furthermore, a performance factor that can evaluate the SVM's accuracy and efficiency is presented, and a quantitative optimization strategy is established for the first time. After the optimization of our synthetic fingerprint discrimination task, the polynomial kernel with a training sample proportion of 5% is the optimized value when the minimum accuracy requirement is 95%. The radial basis function (RBF) kernel with a training sample proportion of 15% is a more suitable choice when the minimum accuracy requirement is 98%
Influence of Incentives on Performance in a Pre-College Biology MOOC
There is concern that online education may widen the achievement gap between students from different socioeconomic classes. The recent discussion of integrating massive open online courses (MOOCs) into formal higher education has added fuel to this debate. In this study, factors influencing enrollment and completion in a pre-college preparatory MOOC were explored. University of California at Irvine (UCI) students of all preparation levels, defined by math Scholastic Aptitude Test (SAT) score, were invited to take a Bio Prep MOOC to help them prepare for introductory biology. Students with math SAT below 550 were offered the explicit incentive of an early change to the biology major upon successful completion of the MOOC and two additional onsite courses. Our results demonstrate that, among course registrants, a higher percentage of UCI students (>60%) completed the course than non-UCI registrants from the general population (<9%). Female UCI students had a greater likelihood of enrolling in the MOOC, but were not different from male students in terms of performance. University students entering with low preparation outperformed students entering who already had the credentials to become biology majors. These findings suggest that MOOCs can reach students, even those entering college with less preparation, before they enter university and have the potential to prepare them for challenging science, technology, engineering, and mathematics (STEM) courses
Amorphous TiO2-supported Keggin-type ionic liquid catalyst catalytic oxidation of dibenzothiophene in diesel
Abstract Supported ionic liquid (IL) catalysts [C n mim]3PMo12O40/Am TiO2 (amorphous TiO2) were synthesized through a one-step method for extraction coupled catalytic oxidative desulfurization (ECODS) system. Characterizations such as FTIR, DRS, wide-angle XRD, N2 adsorption–desorption and XPS were applied to analyze the morphology and Keggin structure of the catalysts. In ECODS with hydrogen peroxide as the oxidant, it was found that ILs with longer alkyl chains in the cationic moiety had a better effect on the removal of dibenzothiophene. The desulfurization could reach 100% under optimal conditions, and GC–MS analysis was employed to detect the oxidized product after the reaction. Factors affecting the desulfurization efficiencies were discussed, and a possible mechanism was proposed. In addition, cyclic experiments were also conducted to investigate the recyclability of the supported catalyst. The catalytic activity of [C16mim]3PMo12O40/Am TiO2 only dropped from 100% to 92.9% after ten cycles, demonstrating the good recycling performance of the catalyst and its potential industrial application
Increased Inequalities in Health Resource and Access to Health Care in Rural China
Both health resources and access to these resources increased after China’s health care reform launched in 2009. However, it is not clear if the inequalities were reduced within rural China, which was one of the main targets in the reform. This study aims to examine the changes in inequalities in health resources and access following the reform. Data came from the routine report of rural counties in every other year from 2008 to 2014. Health professionals and hospital beds per 1000 population were used for measuring health resources, and the hospitalization rate was used for access. Descriptive analysis and the fixed effect model were used in this study. Health resources and access increased by about 50% between 2008 and 2014 in rural China. The counties in richer quintiles got more health resources and hospitalizations. As for health professionals, the absolute differences between the richer and the poorest quintile were significantly enlarging in 2014 when compared to 2008. Regarding the hospitalization rate, the differences between the richest and the poorest quintile showed no significant change after 2012. In sum, absolute inequalities of health resources were increased, while that of health utilization kept constant following China’s health care reform. The reform needs to continually recruit qualified health workers and appropriately allocate health infrastructures to strengthen the capacity of the health care system in the impoverished areas
The relationship between training samples proportion and discrimination accuracy on different kernel functions.
<p>The relationship between training samples proportion and discrimination accuracy on different kernel functions.</p