bluuebunny/crossref_metadata_2025_split huggingface dataset:
The effects of Fe- and Mn-oxides and imogolite in the presence of kaolinite on organic nitrogen mineralization and soil enzyme activities
Authors: Rakhsh Fatemeh , Golchin Ahmad , Nelson Paul N. , Agha Ali Beheshti Al 
Published: February 2022

Abstract

Clay minerals and metal oxides play an important role in controlling the decomposition of soil organic matter and the mineralization of organic nitrogen. To study the effects of clay content and composition on mineralization of organic nitrogen, an incubation experiment was carried out. In the experiment, mineralization of organic nitrogen from alfalfa residues, activities of acid and alkaline phosphatase and CM-cellulase, and microbial biomass nitrogen were measured in mixtures of sand, kaolinite (0, 15, 30 or 45%) and non-layered colloids (NLCs, being goethite, manganese oxide or imogolite at a kaolinite:NLC ratio of 1:0, 5:1 or 10:1), with pure sand as the control, which were inoculated with microbes from natural soil and incubated at 23°C in the dark at 60% of water holding capacity for 180 days. Mineralization of organic nitrogen and enzyme activity decreased, but microbial biomass nitrogen increased as the contents of kaolinite and NLCs increased. There was an inverse relationship between the specific surface area of the mixtures and the enzyme activity and mineralization of organic nitrogen. Thus, the decreased mineralization of organic nitrogen, despite an increase in microbial biomass, appears to have been due to inactivation of extracellular enzymes by adsorption to the surfaces of kaolinite and NLCs, and perhaps also decreased accessibility of organic nitrogen substrate molecules due to adsorption. The microbial biomass nitrogen increased as the water holding capacity of the mixtures increased, indicating the importance of water-filled pores for accommodating an active microbial biomass and protecting it from desiccation and predators.
Thermal performance analysis of a tilted single glazed flat plate collector considering the effect of clear sky black body temperature under different ambient conditions encountered in Delhi.
Authors: Kumar Sachin 
Published: February 2022

Abstract
The present study concerns with the thermal analysis of a flat plate collector covered with a single glass having a tilted surface facing south, located at Delhi (28064’ N, 77012’ E), India under different operating and climate conditions. Solar radiations falling on the tilted surface were noted throughout the year and based on the availability of these solar radiations optimum tilt angle was estimated by using empirical relation for every month of a year. The lowest optimum tilt angle was estimated for June (5.260), and the highest was estimated for December (51.950) with an overall optimum tilt angle of 31.10 for a year. The maximum variation in estimated values of UL is 11% and the collector heat efficiency factor has a maximum variation of 1.24% to 2.52%. Further, the use of the Swinbank equation provides the lower value of heat loss which in turn provides the highest value of useful heat gain and thus the efficiency is 4.596% to 9.94% higher than the efficiency calculated by using Angstrom relation which gives the lowest value of efficiency.
Sources, enumerations and inactivation mechanisms of four emerging viruses in aqueous phase
Authors: Hossain Fahim 
Published: February 2022

Abstract
Emergence and re-emergence of four types of severely infectious viruses have claimed significant numbers of lives when anthropogenic activities contribute to the mutagenesis of these pathogens and infectivity of these pathogens has been noticeably altered. However, both point and non-point sources can transport these viruses in water treatment and resource recovery facilities (RRF) where the presence of these pathogens in aerosolized form or in suspension can cause astronomical public health concerns. Hence, numerous scientific studies have been reviewed to comprehend the possible inactivation mechanisms of those viruses in aqueous phase where thermal-, photo-, and chemical-inactivation have confirmed their effectiveness in restraining those viruses and inactivation mechanisms are the major focuses to apprehend the quick and cost-effective virus removal process from water and RRF. Although practical applications of nano-sized disinfectants have challenged researchers, those disinfectants can completely kill the viruses and hamper RNA/DNA replication without any sign of reactivation or repair. Moreover, limitations and future research potential are discussed so that efficacious strategic management for a treatment facility can be developed at the forefront of fighting tactics against an epidemic or a pandemic. Enumerations, besides state-of-the-art detection techniques with gene sequences, are mentioned for these viruses.
Modeling bulk surface resistance and evaluation of evapotranspiration using remote sensing and MATLAB
Authors: Shekar N. C. Sanjay , Raju B. C. Kumar 
Published: February 2022

Abstract
In developing countries, computation of actual evapotranspiration (AET) is challenging due to the lack of ground-based flux measurement data. The estimation of AET is crucial for water resources management involving the allocation of water for different land use/land cover (LULC) classes. The study's novelty was mapping pixel-by-pixel spatial variations of bulk surface resistance and evaluating the derived actual evapotranspiration in a sub-humid tropical river basin where flux tower data was lacking for validation. This study aimed to map bulk surface resistance and evaluate the estimated AET by global evapotranspiration data product (MOD16A2). Moderate Resolution Imaging Spectroradiometer (MODIS) data products, including land surface reflectance (LSR), land surface temperature (LST) and leaf area index (LAI) data, were used as input in MATLAB for mapping pixel-wise variations to analyze the seasonal variations in bulk surface resistance (rs) and AET in pre-monsoon and post-monsoon seasons during the years 2019 and 2012. The years 2019 and 2012 were selected because 2019 experienced a relatively wet pre-monsoon and post-monsoon, whereas 2012 experienced the opposite conditions, which proved useful when interpreting variations that are influenced by wetness conditions. Overall, the results indicated significant variability in the rs and AET for different LULC classes. MOD16A2 AET was determined to be slightly higher than the LULC classes' estimated AET. This study's MODIS satellite data products provided information on surface characteristics at a reasonable resolution. This permitted the identification of differences in LULC classes and changes in surface characteristics by season and wetness conditions, which are helpful when estimating AET.
A new precipitation forecast method based on CEEMD-WTD-GRU
Authors: Zhang Xianqi , Duan Bingsen , He Shaoyu , Wu Xilong , Zhao Dong 
Published: February 2022

Abstract
The simulation of precipitation changes can provide references for the prediction and prevention of flood disasters, and has guiding significance for the comprehensive utilization of regional water resources. Precipitation forecasting is difficult due to the randomness and uncertainty of precipitation events. CEEMD can effectively overcome modal aliasing and white noise interference. The WTD process has obvious denoising effects on the original signal. GRU can effectively solve long-term memory and reflection. Based on the advantages of problems such as gradients in propagation, a CEEMD-WTD-GRU precipitation prediction coupling model is constructed. The second decomposition of CEEMD-WTD-GRU can more effectively extract complex time series information. The time series forecasting provided a new method, which effectively improved the accuracy of the forecast and applied it to the forecast of monthly precipitation in Shanghai. The research results show that the average absolute error of the CEEMD-WTD-GRU model is 3.86, the average relative error is 3.30%, and the Nash efficiency coefficient is 0.99. The prediction accuracy is better than the CEEMD-WTD-GRU model without noise reduction, the CEEMD-LSTM model and GRU model, which shows that it has strong nonlinear and complex process learning ability in hydrological factor simulation, and can be used for regional precipitation prediction.
Antiproliferative Effects of Artabotrys odoratissimus Fruit Extract and its Bioactive
Fraction through Upregulation of p53/γH2AX Signals and G2/M Phase Arrest in
MIA PaCa-2 Cells
Authors: Pargi Meghana , Jain Raviraj Sandeep Kumar , Narayanappa Prashanth , Urumarudappa Santhosh Kumar J. , Malleshappa Pallavi , Malleshappa Kumaraswamy Honnenahally 
Published: February 2022

Background:
Artabotrys odoratissimus (Annonaceae) is a medicinal and ornamental plant widely cultivated
in Southeast Asia for its famous ylang ylang essential oil. The fruits of this plant are used for health benefits, but very
little is studied about the bioactive principles, their role in regulating oxidative stress and tumour progression.

Objective:
The study aimed to evaluate the antiproliferative effects of fruit extract of Artabotrys odoratissimus and its
bioactive fraction using cell-based assays.

Methods:
The free radical scavenging and antiproliferative effects of Artabotrys odoratissimus fruit ethyl acetate
(FEA) extract and its bioactive fraction were evaluated using cell viability assays, colony formation assay, double
staining assay, reactive oxygen species (ROS) assay, comet assay, cell cycle analysis, and western blotting.

Results:
The extract showed phenolic content of 149.8±0.11μg/mg Gallic acid equivalents and flavonoid content of
214.47±4.18 μg/mg Quercetin. FEA showed an IC50 value of 76.35 μg/ml in the ABTS assay and an IC50 value of
134.3±7.8 μg/ml on MIA PaCa-2 cells. The cells treated with 125 μg/ml and 250 μg/ml FEA showed increased apoptotic
cells in Double staining assay, DNA damage during comet assay, enhanced ROS, and cell cycle arrest at G2M
phase at 125 μg/ml and 250 μg/ml. The active fraction AF5 showed an IC50 value of 67±1.26 μg/ml on MIA PaCa-2
cells during MTT assay, displayed potential antiproliferative effects, and showed a marked increase in the expression
of γH2AX and p53.

Conclusion:
These results prove that the fruit extract and the bioactive fraction demonstrate oxidative stress-mediated
DNA damage, leading to apoptosis in the MIA PaCa-2 cell line.
Disease Progression of Hypertrophic Cardiomyopathy: Modeling Using Machine Learning
Authors: Pičulin Matej , Smole Tim , Žunkovič Bojan , Kokalj Enja , Robnik-Šikonja Marko , Kukar Matjaž , Fotiadis Dimitrios I , Pezoulas Vasileios C , Tachos Nikolaos S , Barlocco Fausto , Mazzarotto Francesco , Popović Dejana , Maier Lars S , Velicki Lazar , Olivotto Iacopo , MacGowan Guy A , Jakovljević Djordje G , Filipović Nenad , Bosnić Zoran 
Published: February 2022

Background
Cardiovascular disorders in general are responsible for 30% of deaths worldwide. Among them, hypertrophic cardiomyopathy (HCM) is a genetic cardiac disease that is present in about 1 of 500 young adults and can cause sudden cardiac death (SCD).

Objective
Although the current state-of-the-art methods model the risk of SCD for patients, to the best of our knowledge, no methods are available for modeling the patient's clinical status up to 10 years ahead. In this paper, we propose a novel machine learning (ML)-based tool for predicting disease progression for patients diagnosed with HCM in terms of adverse remodeling of the heart during a 10-year period.

Methods
The method consisted of 6 predictive regression models that independently predict future values of 6 clinical characteristics: left atrial size, left atrial volume, left ventricular ejection fraction, New York Heart Association functional classification, left ventricular internal diastolic diameter, and left ventricular internal systolic diameter. We supplemented each prediction with the explanation that is generated using the Shapley additive explanation method.

Results
The final experiments showed that predictive error is lower on 5 of the 6 constructed models in comparison to experts (on average, by 0.34) or a consortium of experts (on average, by 0.22). The experiments revealed that semisupervised learning and the artificial data from virtual patients help improve predictive accuracies. The best-performing random forest model improved R2 from 0.3 to 0.6.

Conclusions
By engaging medical experts to provide interpretation and validation of the results, we determined the models' favorable performance compared to the performance of experts for 5 of 6 targets.
Development and Validation of the Adolescent Media Health Literacy Scales: Rasch Measurement Model Approach
Authors: Fleary Sasha A 
Published: February 2022

Background
High media use has been implicated in negative social and health outcomes among adolescents. Therefore, it is critical that adolescents develop skills to healthily engage with media content. Media health literacy (MHL), skills for assessing and responding to health-related media content, and potentially targetable moderators for the relationship between media use and health-related outcomes are understudied in adolescents. The lack of MHL assessment tools may have contributed to this research gap.

Objective
This study aimed to develop and validate test-based scales of adolescents’ MHL.

Methods
The items developed were vetted iteratively via community reviews and cognitive interviews to establish content and face validity. Adolescents (N=355) completed a questionnaire that included the revised MHL items. The scales (Recognition/Identification, Influence/Critical Analysis, and Action/Reaction) were validated using Rasch measurement models. Convergent validity was assessed by correlating the summed scores of the three scales with existing functional and internet-related health literacy measures. Criterion validity was assessed by modeling logistic regressions for predicting health literacy–related behaviors from each scale after controlling for demographics. Effect sizes were estimated, and a short form was also validated.

Results
The final MHL scales (Recognition/Identification, Influence/Critical Analysis, and Action/Reaction) fit their Rasch models. The 9-item Recognition/Identification and 9-item Influence/Critical Analysis scales had good convergent validity with functional and internet-related health literacy measures and were positively related to reading instructions before taking medicines and questioning the truthfulness of health information found online. The 12-item MHL Scales-Short Form also had good convergent and criterion validity. However, convergent and criterion validity were not established for the 3-item Action/Reaction Scale.

Conclusions
The Recognition/Identification and Influence/Critical Analysis scales and the MHL Scales-Short Form may be used to determine the impact of MHL on media use and health outcome relationships and ultimately inform the development of interventions and policies to affect these relationships in multiple settings.
Continuous Glucose Monitoring Data Sharing in Older Adults With Type 1 Diabetes: Pilot Intervention Study
Authors: Allen Nancy A , Litchman Michelle L , Chamberlain James , Grigorian Ernest G , Iacob Eli , Berg Cynthia A 
Published: February 2022

Background
Family members or friends (care partners [CPs]) of older adults with type 1 diabetes (T1DM) regularly become part of the diabetes care team, but they often lack knowledge about how to become involved to prevent hypo- and hyperglycemia. Continuous glucose monitoring (CGM) allows a person with diabetes to see their glucose levels continuously and to receive predictive alerts. A smartphone data-sharing app called the Follow app allows the person with diabetes to share continuous glucose numbers with others and to receive predictive alerts of impending hypo- and hyperglycemia. However, there are barriers to sharing this continuous glucose level data with CPs.

Objective
This study aimed to address the barriers to sharing CGM data. Our objective was to examine the feasibility of using CGM with the Follow app and a data-sharing intervention called SHARE plus in older adults with T1DM and their CPs. SHARE plus includes dyadic communication strategies, problem-solving strategies, and action planning to facilitate CGM data sharing.

Methods
Older adults with T1DM (n=20) and their CPs (n=20) received the SHARE plus intervention at baseline. People with diabetes wore the CGM for 12 weeks while sharing their glucose data using the Follow app with CPs. Feasibility data were analyzed using descriptive statistics.

Results
The SHARE plus intervention was feasible and was associated with high self-reported satisfaction for people with diabetes and their CPs as well as high adherence to CGM (mean 96%, SD 6.8%). Broad improvements were shown in the diabetes-related quality of life through the use of CGM in people with diabetes and their CPs. Although the majority of people with diabetes (11/20, 55%) were willing to share hyperglycemia data, several chose not to. The majority of people with diabetes (14/20, 70%) were willing to talk about glucose numbers with a CP.

Conclusions
Older adults with T1DM and their CPs identified having someone else aware of glucose levels and working together with a partner on diabetes self-management as positive aspects of the use of the SHARE plus intervention. Clinicians can use these results to provide data sharing coaching in older adults and their CPs.
Cascade of HIV Prevention, Care, and Treatment Services in Morocco in 2019
Authors: Sakhri Noureddine 
Published: February 2022

Background
The HIV care cascade is a way to show the proportion of people living with HIV (PLHIV) engaged at each stage of HIV care. Analyzing an HIV testing, care, and treatment cascade provides a framework for evaluating and improving service delivery.

Objective
The objective of this study is to analyze the continuums of HIV prevention, care, and treatment services at the national level in Morocco for the period 2015-2019.

Methods
This is a retrospective study concerning the reference centers for HIV care in Morocco carried out in 2019. Three types of cascades of HIV prevention and care were studied: a transversal cascade at the national level (2019), a longitudinal cascade for newly diagnosed PLHIV (between 2015 and 2017), and a cascade of prevention of mother-to-child transmission of HIV (PMTCT) among pregnant women (2016-2017).

Results
For the transversal cascade of the year 2019, the objectives of the three 90s were achieved except for the 1st 90 with a difference of 12%. For the longitudinal cascade after the start of treatment between 2015-2017, retention under treatment at 48 months was 83.3%, at 36 months was 83.8%, and at 24 months 91.0%. The 48-month loss to follow-up rate was 12.5%; 7.0% at 36 months; and 4.0% at 24 months. More than 90% of PLHIV started antiretrovirals within 3 months of diagnosis. The 2016-2017 PMTCT cascade conducted on 13 pregnant women according to available data indicated the absence of transmission of HIV from mothers to their children.

Conclusions
Our 2019 HIV cascade study demonstrated several successes. The achievement of the three 90s except for the first objective (of people who know their status), good retention of PLHIV in long-term treatment, and the success of PMTCT especially since Morocco aims to validate the elimination of mother-to-child transmission.
Computational Drug Design of Novel Small Molecule Inhibitors for Therapy in Pancreatic Ductal Adenocarcinoma
Authors: Shrivastava Aryansh 
Published: February 2022

Today, pancreatic ductal adenocarcinoma, the most common form of
pancreatic cancer, is one of the deadliest cancer types and remains
largely unresolved. Through my research, I engineer a class of novel
small molecule ligands to cure the disease by inhibiting its central
carcinogenic pathway, taking the unique approach of applying the
framework of targeted drug therapy and leveraging computer-aided
techniques.
The target molecule for which drug design is employed is xCT, a protein
embedded in the ductal cell membrane that enables cancer cells to
survive without a nutrient supply and kills normal cells of the
pancreas. All viable drug candidate ligands must be engineered to have a
complementary structure and biochemistry to the binding site of xCT.
Starting with some known ligands of xCT to first identify the binding
site and binding mode, I conduct guided substituent recombination based
on the analysis of hydrophobicity and Coulombic surfaces as well as
intermolecular interactions through computational docking simulations.
In doing so, I employ industry-grade softwares including Chimera (to
visualize 3D structures), Avogadro (to minimize free energies and infer
3D chemical structures), ChemDraw (to draw 2D chemical structures),
AutoDockTools (to visualize the location of the binding site), AutoDock
Vina (to perform docking simulations), and the SeaWulf computational
cluster (for intensive, high accuracy computations).
A total of 1461 novel results are tabulated, and the top two drug
candidates among them are found to be CID 136204070 and 135564873, the
best one among them CID 135564873. These can be used by drug industries
to create new targeted drug therapies for pancreatic cancer, increasing
the survival rate of the disease and saving countless lives through
proactive treatment despite diagnostic delays. I’ve computationally
ensured the absorption, distribution, metabolism, excretion, and
toxicity results for the final drug candidates, and all of the relevant
quantities are computationally verified through well-defined
biochemistry lab procedures for the final ligand molecules and found to
be very reliable for drug candidacy.
I did this project through the Simons Summer Research Program at Stony
Brook University as a Simons Fellow and paid research intern, under the
guidance of Distinguished Professor Iwao Ojima and student mentors Adam
Taouil and Frank Wang.
Does Board Demographic Diversity Enhance Cognitive Diversity and Monitoring?
Authors: Kang Jun-Koo , Kim Seil , Oh Seungjoon 
Published: February 2022

ABSTRACT
We examine whether board demographic diversity enhances cognitive diversity (measured as director dissent in the boardroom) and monitoring. At the director level, we find that individual directors who are dissimilar relative to other board members in terms of tenure and experience are more likely to dissent. At the board level, boards composed of directors who have heterogenous tenure, experience, and gender are more likely to dissent. We also find that stock market reactions to director resignation announcements are more negative for directors who have ever dissented than for other directors. Moreover, following dissent-driven proposal rejections, firms experience an improvement in value and internal governance and a decrease in risk. The results suggest that directors who have diverse qualifications and skillsets as well as the inclusion of female directors enhance cognitive diversity, and that this enhanced cognitive diversity helps increase firm value and monitoring effectiveness.
JEL Classifications: G30; G32; G34.