bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multi-step solar UV index prediction using deep learning methods
Authors: Al-Musaylh Mohanad S , Ghimire Sujan , Al-Daffaie Kadhem , Ali Mumtaz , Deo Ravinesh C , Downs Nathan , Igoe Damien P. , Parisi Alfio V 
Published: January 2023

AbstractThe impact of ultraviolet (UV) radiation on public health is severe and can cause sunburn, skin aging and cancer, immunosuppression, and eye damage. Minimization of exposure to solar UV is required in order to reduce the risks of these illnesses to the public. Greater public awareness and a prediction of the ultraviolet index (UVI) is considered an essential task for the minimization of solar UV exposures. This research has designed artificial intelligence based deep learning models to predict multistep UVI index. It has developed a convolutional neural network integrated with long short-term memory network (CLSTM) as the main model to forecast UVI for Brisbane with latitude − 27.47 and longitude 153.02, the capital city of Queensland, Australia. Solar zenith angle (SZA) data were used together with UVI as inputs in the CLSTM for 10-min, 30-min and 60-min UVI prediction. The CLSTM model was benchmarked against long short-term memory network (LSTM), convolutional neural network (CNN), Deep Neural Network (DNN), multilayer perceptron (MLP), extreme learning machine (ELM), random forest regression (RFR), Extreme Gradient Boosting (XGB), and Pro6UV Deterministic models. The experimental results showed that the CLSTM model outperformed these models withRMSE = 0.3817,MAE = 0.1887,RRMSE = 8.0086%,MAPE = 4.6172% andAPB = 3.9586 for 10-min prediction. In addition to that, these metrics for 30-min and 60-min prediction wereRMSE = 0.4866/0.5146,MAE = 0.2763/0.3038,RRMSE = 10.4860%/11.5840%,MAPE = 8.1037%/9.6558% andAPB = 5.9546/6.8386, respectively. Thus, the CLSTM model can yield improved UVI prediction for both the public and the government agencies.
Inequity in Mortality Rates and Potential Years of Life Lost caused by COVID-19 in the Greater Santiago, Chile
Authors: Ayala Andrés , Vargas Claudio , Elorrieta Felipe , Dintrans Pablo Villalobos , Maddaleno Matilde 
Published: January 2023

Abstract

Background
Several studies have shown that in Chile income inequality is relevant in explaining inequities in health outcomes. The COVID-19 pandemic has also had a non-neutral impact, with higher mortality rates in municipalities with lower socioeconomic status.
Methods
We study inequity in mortality based on Potential Years of Life Lost (PYLL) in 34 urban municipalities of the Metropolitan Region (Greater Santiago) and analyze its evolution between 2018 and 2021 and by COVID-19 waves. In order to compare the results obtained for PYLL, we also computed the mortality rates adjusted by direct standardization. In addition, we used the concentration index to measure the health inequalities between municipalities.
Results
In the first year of the pandemic, the absolute PYLL and the crude mortality rate for all causes of death showed an increase of 13.6% and 19.8%, respectively. Moreover, 409,086 years of life were prematurely lost in 2020, one-fifth of them due to COVID-19. The concentration indices show signs of inequality in both mortality rates and PYLL, where it is more pronounced when calculating the latter measure.
Conclusions
Results show that the excess deaths due to the COVID-19 pandemic affected the most economically disadvantaged municipalities, and even more so the young people in those places.
Evaluation of the efficacy of household insecticides against Aedes aegypti in Sri Lanka
Authors: Sānu M. Nowmaan S. , Fernando Sachini D. , De Silva B. G. D. Nissanka K. 
Published: January 2023

Abstract
Background: Mosquito coils and liquid vaporizers are commonly consumed as household insecticides against mosquitoes in Sri Lanka, but their efficacy have not been evaluated. The current study is the first step in evaluating three brands of mosquito coils and liquid vaporizers that are commercially available in the Sri Lankan market against the major dengue vector Aedes aegypti and to find the impact of mosquito knock-down resistance (kdr) on the efficacy of household insecticides.
Methods: WHO recommended “Peet-Grady” protocol was followed to evaluate both field and reference strains and the genomic mutation responsible for knock-down resistance (kdr) was examined.
Results: Mean knock-down percentage of field strain after 60 minutes of exposure for d-trans-allethrin (w/w 0.12%), dimefluthrin (w/w 0.01%) and metofluthrin (w/w 0.005%) mosquito coils and prallethrin (w/v 1.24%), prallethrin (w/v 1.26%) and transfluthrin (w/v 0.9%) liquid vaporizers ranged from 0 - 10%. A higher percentage of knock-down observation to field strain was recorded from dimefluthrin (w/w 0.01%) (5.5%) mosquito coil and transfluthrin (w/v 0.9%) (5.0%) liquid vaporizer. All three brands of mosquito coils and liquid vaporizers were able to kill less than 5% of field strain and more than 80% of reference strain. KT50 and KT95 values were calculated only for dimefluthrin (w/v 0.01%) mosquito coil and transfluthrin (w/v 0.9%) liquid vaporizer while the remaining tested products showed less than 5% knock-down. The mutant allele (Cys) frequency was 0.72 in mosquitoes that resist household insecticide exposure and 0.67 in susceptible and the mutant allele (Gly) frequency was 0.1 in survived mosquitoes and 0.29 in dead mosquitoes.
Conclusions: The present study provides experimental evidence on the development of pyrethroid resistance role in reducing the efficacy of commercial household insecticides as tested all product lost their efficacy against Sri Lankan Ae. aegypti mosquitoes.
Assessment of Arsenic levels in rice brands sold in Kampala. An experimental study to demonstrate the modifying effect of boiling, soaking and washing
Authors: Nfambi Joshua , Lugaajju Allan , Namaganda Agnes , Acen Ester L. , Kalyesubula Robert , Sembajwe Lawrence F. 
Published: January 2023

Abstract
Background: Arsenic is one of the major toxic metals in the environment that is also known to be carcinogenic with several other health side effects in human beings. It can cause both acute and chronic toxicity depending on the doses available or duration of exposure in the human body. The major sources of arsenic exposure to humans include; via contaminated water, food and inhalation of arsenic dust from polluted air from car-fumes or industrial wastes and mining/ smelting grounds. Due to the fact that high levels of arsenic have been reported in rice from major rice-growing countries in Asia and rice being a major stapple food in Uganda, some of which is imported, this study aimed at determining the concentration of total arsenic in various rice brands sold in Uganda.
Methods: Various rice brands weresampled from different supermarkets and grocery shops, taken to the laboratory and analyzed for arsenic using atomic absorption spectrometry. The arsenic concentration in the rice were determined following boiling or overnight soaking in plenty of water to see if these two approaches can help in significantly reducing the arsenic in the rice. The concentration of arsenic in the various brands of rice were compared using an unpaired t-test after setting a p-value of ≤0.05 as significant.
Results: The York taste rice brand had the lowest arsenic levels of 1.4±0.0002 ppm and Zhong Yi rice brand had the highest levels of 2.4±0.004 ppm. The tap water used to boil, soak and wash the rice brands had much higher arsenic levels of 3.5±0.000003 ppm, which caused increased retention of the heavy metal in the rice.
Conclusion: Rice brands sold in Kampala city seem to have higher than acceptable arsenic levels than what is recommended by WHO or American food and drug authority. The high levels of arsenic in tap water used in preparing the rice causes increased retention of the metal on boiling, soaking and washing. It is therefore, necessary to routinely monitor for arsenic levels in the rice on the market and domestic water sources so as to protect the general public from arsenic toxicity.
Quantity and quality of job creation in renewable energy and energy efficiency: A review of international evidence
Authors: Hanna Richard , Heptonstall Philip , Gross Robert 
Published: January 2023

Abstract
In this paper we present findings from a systematic review on job creation, quality, and skills, focusing on decarbonisation in the energy sector. We compare a range of gross job employment factors which indicate that overall, investment in renewable energy and energy efficiency can deliver more jobs than gas or coal power generation. In addition, we review a subset of recent studies which estimate the net employment effects of decarbonisation in the energy sector at a national scale, across various international contexts. These national studies largely agree that the most likely outcome over the next few decades is a modest net positive creation of jobs and moderate economic growth. In certain regions within these countries, jobs in fossil fuel industries may be lost faster than the pace at which low carbon energy sectors can offer new employment. There may be mismatches between regions where displaced workers live and where new opportunities become available, which may be a barrier to accepting alternative employment even if former workers have the requisite skills. In these cases national government transition plans are recommended, co-ordinated with local governments, to manage the impacts of displacement from carbon intensive sectors and respond to the need to build a new low carbon workforce including through skills development and training. We highlight a lack of metrics and data in the literature on job quality, skills, and the geographic distribution of employment impacts in decarbonising energy systems, and these should be priority areas for further research.
Commemorative Stamps as a Recognition Tool: A Cross-Sectional Analysis
Authors: Galliford Patricia , Chan Ho Fai , Torgler Benno 
Published: January 2023

Abstract
Commemorative stamps have a place in the cultural, economic, and geopolitical status of a nation; and the nature of what is printed on stamps is very much a reflection of the culture, regime, and values of a country. Whilst commemorative stamps can be a source of celebration for monuments, flora and fauna, and key points in a nation’s history; they are also a source of recognition, designed to publicly celebrate and showcase the contribution of key figures based on their performance in areas deemed significant to the nation’s culture and evolution. In this empirical study, we analyse commemorative stamp data in a cross-sectional setting to understand key determinants that shape their provision. The award literature has developed some propositions that so far have not been tested empirically. We find strong evidence that the political process strongly influences the use of postage stamps as a recognition tool. The political regime as well as governance matter. For example, controlling for regime, more corrupt countries are more likely to use stamps to recognize personalities. On the other hand, more democratic regimes are more frequently using stamps as a recognition tool. We also find that cultural factors and ideologies show substantial heterogeneity in their influence while factors such as fractionalization or income inequality do not seem to matter. Factors such as personal and impersonal pro-sociality or creativity seemed to reduce the need for stamps as a recognition tool, while other factors such as market orientation, individualism, or traditionalism encourage the use of stamps to recognize individuals. Overall, we find that some results are consistent with the theoretical propositions while others are not, requiring more empirical evidence around awards and a better understanding of how stamps differ from other recognitions.
Profiling of Aspergillus species’ metabolites in maize using different analytical approaches
Authors: Ngum Nji Queenta , Christianah Adetunji Modupeade , Mulunda Mwanza 
Published: January 2023

Abstract
Mycotoxin contamination of food has become a global food safety issue mainly as a result of climate change. Mycotoxin estimation is crucial for their management plan as it is difficult to manage what cannot be quantified. Choosing the right analytical technique in mycotoxin quantification is essential in acquiring accurate data as mycotoxins occur in minute concentrations. Good, feasible and sensitive techniques are therefore needed for mycotoxin detection at such minute concentrations. The aims of this work are to compare the efficiency of HPLC and LC-MS/MS techniques for mycotoxin detection as well as assess the diversity of Aspergillus mycotoxins in maize. One hundred and twenty-three maize samples were analyzed using the HPLC and the LC-MS/MS techniques. Both methods had acceptable LOD, LOQ as well as recovery rates. Secondary metabolites such as 3-Nitropropionic acid and sterigmatocystin which are of safety concerns were detected in South African maize among others. Aspergillus species could be producing other unfamiliar metabolites that are uncounted for that might be underestimated contributors of toxicity to humans and animals. The co-occurrence of multiple toxins in food matrices requires multi-analyte detection techniques, therefore both methods will be suitable for monitoring maize quality, as the HPLC is suitable for the detection of major mycotoxin while LC-MS/MS for minor metabolites.
Increased KCNN4 expression related to poor survival in lower grade glioma
Authors: Lehrer Steven 
Published: January 2023

Abstract
Background
Networks of glioma cells are linked to small groups of pacemaker cells in which levels of calcium ions pulse periodically, driving a signal through the network that causes tumor growth. Using inhibitors, one study blocked the activity of the Ca2+ activated potassium-channel protein KCa3.1 in in vitro models and mice, preventing proliferation of glioma cells and tumor expansion. Marked reduction of tumor cell viability occurred within the entire network, as well as reduced tumor growth in mice and extended animal survival.
Methods
KCa3.1 is encoded by the gene KCNN4 (Potassium Calcium-Activated Channel Subfamily N Member 4) on chromosome 19q13.31. We used the Cancer Genome Atlas (TCGA) to evaluate the effect of KCNN4 on human glioma survival in the TCGA Lower Grade Glioma (LGG) dataset.
Results
In humans KCNN4 is prognostic in glioma: high expression is unfavorable. In addition, KCNN4 copy number variations are prognostic. Increased masked copy number segments are unfavorable in lower grade glioma. KCNN4 is lost in gliomas with the 1p 19q codeletion, which may explain in part the comparatively favorable prognosis of 1p 19q codeletion tumors.
Conclusion
Our finding of increased KCNN4 expression related to poor survival in human lower grade glioma suggests that development of novel therapies, such as KCa3.1-inhibiting drugs, might be worthwhile.
Modified Synthesis and Isolation of an Advanced Intermediate of Remdesivir
Authors: Mohite Dhanaji M. , Pandey Arjun P. , Chavhan Pandurang M. 
Published: January 2023

Abstract:
Synthesis and isolation of an advanced intermediate (S)-2-Ethylbutyl 2-(((S)-(4-
nitrophenoxy) (phenoxy) phosphoryl) amino) propanoate (1b), which is being used for the
manufacture of the prodrug diastereoisomer 1d called Remdesivir have been carried out in
high yield with efficient stereoselectivity. The isolated advanced intermediate 1b was a diastereoselective
nucleoside phosphoramidate prodrug used as an antiviral agent having a mixture
of two (SS) and (SR) diastereomers with stereocenter at phosphorus, which was purified
by converting into a more stable diastereoselective isomer (SS) by simple physical fractional
crystallization process, resulting in an improved yield of ~45%. The recrystallization has been
afforded diastereomerically in 99% pure (SS)-isomer 1b. The 1H NMR characterization data
confirm the (SS)-isomer (1b). The developed process holds significant potential for large-scale
reactions relatively with commercially available low-cost solvents and co-solvents, resulting in an alternative
cheaper process.
The Semantics of COVID-19 Web Data: Ontology Learning and Population
Authors: Sharma Sumit , Jain Sarika 
Published: January 2023

Background:
The acquisition and exchange of meaningful, integrated, and accurate
information are at the forefront of the combat against COVID-19; still, there are many countries
whose health systems are disrupted. Moreover, no one is adequately equipped for COVID-19
contingencies. Many organizations have established static information systems to manage the information.
This fact presents numerous issues, including delays, inconsistencies, and inaccuracies
in COVID-19 information collected for pandemic control and monitoring.

Objective:
This paper presents a semantic representation of COVID-19 data, a domain ontology
to facilitate measurement, clarification, linking, and sharing. We automatically generate a computer-
intelligible knowledge base from COVID-19 case information, which contains machineunderstandable
information. Furthermore, we have anticipated an ontology population algorithm
from tabular data that delivers interoperable, consistent, and accurate content with COVID-19 information.

Methods:
We utilized the tabula package to extract the tables from PDF files and user NLP libraries
to sort and rearrange tables. The proposed algorithm was then applied to all instances to
automatically add to the input ontology using the Owlready Python module. Moreover, to evaluate
the performance, SPARQL queries were used to retrieve answers to competency questions.

Results:
When there is an equivalence relationship, the suggested algorithm consistently finds the
right alignments and performs at its best or very close to it in terms of precision. Moreover, a
demonstration of algorithm performance and a case study on COVID-19 data to information
management and visualization of the populated data are also presented.

Conclusion:
This paper presents an ontology learning/matching tool for ontology and populating
instances automatically to ontology by emphasizing the importance of a unit's distinguishing features
by unit matching.
Changes in Mobile Health Apps Usage Before and After the COVID-19 Outbreak in China: Semilongitudinal Survey
Authors: Yang Le , Wu Jiadong , Mo Xiaoxiao , Chen Yaqin , Huang Shanshan , Zhou Linlin , Dai Jiaqi , Xie Linna , Chen Siyu , Shang Hao , Rao Beibei , Weng Bingtao , Abulimiti Ayiguli , Wu Siying , Xie Xiaoxu 
Published: January 2023

Background
Mobile health (mHealth) apps are rapidly emerging technologies in China due to strictly controlled medical needs during the COVID-19 pandemic while continuing essential services for chronic diseases. However, there have been no large-scale, systematic efforts to evaluate relevant apps.

Objective
We aim to provide a landscape of mHealth apps in China by describing and comparing digital health concerns before and after the COVID-19 outbreak, including mHealth app data flow and user experience, and analyze the impact of COVID-19 on mHealth apps.

Methods
We conducted a semilongitudinal survey of 1593 mHealth apps to study the app data flow and clarify usage changes and influencing factors. We selected mHealth apps in app markets, web pages from the Baidu search engine, the 2018 top 100 hospitals with internet hospitals, and online shopping sites with apps that connect to smart devices. For user experience, we recruited residents from a community in southeastern China from October 2019 to November 2019 (before the outbreak) and from June 2020 to August 2020 (after the outbreak) comparing the attention of the population to apps. We also examined associations between app characteristics, functions, and outcomes at specific quantiles of distribution in download changes using quantile regression models.

Results
Rehabilitation medical support was the top-ranked functionality, with a median 1.44 million downloads per app prepandemic and a median 2.74 million downloads per app postpandemic. Among the top 10 functions postpandemic, 4 were related to maternal and child health: pregnancy preparation (ranked second; fold change 4.13), women's health (ranked fifth; fold change 5.16), pregnancy (ranked sixth; fold change 5.78), and parenting (ranked tenth; fold change 4.03). Quantile regression models showed that rehabilitation (P75, P90), pregnancy preparation (P90), bodybuilding (P50, P90), and vaccination (P75) were positively associated with an increase in downloads after the outbreak. In the user experience survey, the attention given to health information (prepandemic: 249/375, 66.4%; postpandemic: 146/178, 82.0%; P=.006) steadily increased after the outbreak.

Conclusions
mHealth apps are an effective health care approach gaining in popularity among the Chinese population following the COVID-19 outbreak. This research provides direction for subsequent mHealth app development and promotion in the postepidemic era, supporting medical model reformation in China as a reference, which may provide new avenues for designing and evaluating indirect public health interventions such as health education and health promotion.
Monitoring School Absenteeism for Influenza-Like Illness Surveillance: Systematic Review and Meta-analysis
Authors: Tsang Tim K , Huang Xiaotong , Guo Yiyang , Lau Eric H Y , Cowling Benjamin J , Ip Dennis K M 
Published: January 2023

Background
Influenza causes considerable disease burden each year, particularly in children. Monitoring school absenteeism has long been proposed as a surveillance tool of influenza activity in the community, but the practice of school absenteeism could be varying, and the potential of such usage remains unclear.

Objective
The aim of this paper is to determine the potential of monitoring school absenteeism as a surveillance tool of influenza.

Methods
We conducted a systematic review of the published literature on the relationship between school absenteeism and influenza activity in the community. We categorized the types of school absenteeism and influenza activity in the community to determine the correlation between these data streams. We also extracted this correlation with different lags in community surveillance to determine the potential of using school absenteeism as a leading indicator of influenza activity.

Results
Among the 35 identified studies, 22 (63%), 12 (34%), and 8 (23%) studies monitored all-cause, illness-specific, and influenza-like illness (ILI)–specific absents, respectively, and 16 (46%) used quantitative approaches and provided 33 estimates on the temporal correlation between school absenteeism and influenza activity in the community. The pooled estimate of correlation between school absenteeism and community surveillance without lag, with 1-week lag, and with 2-week lag were 0.44 (95% CI 0.34, 0.53), 0.29 (95% CI 0.15, 0.42), and 0.21 (95% CI 0.11, 0.31), respectively. The correlation between influenza activity in the community and ILI-specific absenteeism was higher than that between influenza activity in community all-cause absenteeism. Among the 19 studies that used qualitative approaches, 15 (79%) concluded that school absenteeism was in concordance with, coincided with, or was associated with community surveillance. Of the 35 identified studies, only 6 (17%) attempted to predict influenza activity in the community from school absenteeism surveillance.

Conclusions
There was a moderate correlation between school absenteeism and influenza activity in the community. The smaller correlation between school absenteeism and community surveillance with lag, compared to without lag, suggested that careful application was required to use school absenteeism as a leading indicator of influenza epidemics. ILI-specific absenteeism could monitor influenza activity more closely, but the required resource or school participation willingness may require careful consideration to weight against the associated costs. Further development is required to use and optimize the use of school absenteeism to predict influenza activity. In particular, the potential of using more advanced statistical models and validation of the predictions should be explored.