bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of growth-promoting agents on saffron yield and quality
Authors: Rastegari Sakineh , Alavi Seyed Mehdi Naser , Mohayeji Mehdi 
Published: June 2023

Abstract

Saffron is an important plant whether in the food or medical industry. So, improving stigma quality and quantity is of special importance. To evaluate the effects of chemical/hormone treatment on saffron yield and stigma quality, its corms were treated with Gibberellic acid, 6-Benzylaminopurine, Salicylic acid, and Potassium nitrate. Some floral traits such as flower fresh weight, stigma length, stigma weight, and some quality traits (crocin, picrocrocin, and safranal) and corms’ total sugar and starch content were measured. The results showed significant differences between control and treatments, in a way that in all floral traits, picrocrocin, and safranal, an improvement was observed in treated corms. Also, corm total sugar and starch content were affected by treatments. Correlation analysis showed a positive relationship in some studied traits such as stigma dry weight and stigma length, stigma dry weight and flower fresh weight (r = 0.410) as well as in picrocrocin and safranal. While, a negative correlation was detected in day-to-flowering and flower fresh weight, day-to-flowering, and safranal. Almost all floral traits had a positive correlation with corms’ starch content and a negative correlation with corms' total sugar. Generally, it could be pointed out that earlier flowering was in a positive relationship with quality and quantity traits in this plant. Consequently, exogenous chemical/hormone treatments in appropriate dosage would lead to earlier flowering and improve saffron yield and quality.
Upland rice grain yield and plant improvement by single and combined beneficial microorganisms
Authors: Nascente Adriano Stephan , Temitope Ishola Zainab , Filippi Marta Cristina Corsi , Cruz Dennis Ricardo Cabral 
Published: June 2023

Abstract
In order to meet the increasing demand of the growing population, rice production must increase through the use of sustainable and environmentally friendly methods. The use of beneficial microorganisms is an important strategy to improve rice production in a sustainable way. The study was carried out to determine the effect of single and combined beneficial microorganism on the development of upland rice. The experiment was performed in greenhouse and arranged in a completely randomized design with 28 treatments and 4 replications. Treatments consisted of rice seeds treated with single and combined multifunctional microorganisms (1 (Serratia marcescens), 2 (Bacillus toyonensis), 3 (Phanerochaete australis), 4 (Trichoderma koningiopsis), 5 (Azospirillum brasilense), 6 (Azospirillum sp.), 7 (Bacillus sp), 8 to 28 (combination of these microorganisms) and 29 (control)). Inoculation of upland rice with sole and combined microorganism on upland rice increased the roots and shoots development, yield components and grain yield of upland rice. The combinations of Bacillus sp. (BRM 63573) and A. brasilense (AbV5), Azospirillum sp. (BRM 63574) + B. toyonensis (BRM 32110) and Phanerochaete australiani (BRM 62389) + Serratia marcenscens (BRM 32114) led to greatest values in roots and shoots development, number of panicles, number of grains per pot, 1000 grains weight and grain yield of upland rice plants. Besides, these microorganisms’ combinations allow great accumulating of nutrients in roots, shoots and grains of upland rice plants. The use of beneficial microorganisms can be adopted for increasing upland rice production.
Enhancing Student Understanding of Rheumatic Disease Pathologies through Augmented Reality: Findings from a Multicenter Trial in Germany
Authors: Pfeil Alexander , Klemm Philipp , Hueber Axel J , Hoffmann Tobias , Weise Tobias , Oelzner Peter , Knop Stefan , Schuster Louis , Müller-Ladner Ulf , Lange Uwe , Wolf Gunter , Schett Georg , Simon David , Kleyer Arnd 
Published: June 2023

Abstract

Objective
The possibility of combining real and virtual environments is driving the increased use of augmented reality (AR) in education, including medical training. The aim of this multi-centre study was to evaluate the students’ perspective on the AR-based Rheumality GO!® app as a new teaching concept, presenting six real anonymised patient cases with rheumatoid arthritis (RA), psoriatic arthritis (PsA), and axial spondyloarthritis (axSpA).
Patients and methods
The study encompassed 347 undergraduate medical students (232 women and 115 men) from four medical universities in Germany (Jena, Bad Nauheim/Gießen, Nuremberg, Erlangen). The course was divided into a theoretical refresher lecture followed by six AR-based cases in each of the three indications presented in the AR app (Rheumality GO!®). All participants evaluated the course after completion, assessing the benefit of the app from a student´s perspective using a questionnaire with 16 questions covering six subject areas.
Results
The use of the AR-based app improved the understanding of pathologies in RA, PsA, and axSpA for 99% of the participants. For 98% of respondents, the concept of AR with real patient data has made a positive impact on the teaching environment. On the other hand, 82% were in favour of the use of virtual tools (e.g. AR) in addition to this conventional approach.
Conclusion
The results of our study showed that from medical students' perspective, an AR-based concept can complement rheumatology teaching in medical school as an effective and attractive tool.
Obesity promotes pancreatic cancer through the ECM-PI3K-AKT signaling axis
Authors: Zhang Xusheng , Ouyang Haoxuan , Chen Long , Ding Lin , Ma Weihu , Chen Bendong 
Published: June 2023

Abstract
Objective To investigate obesity signature genes as potential biomarkers of pancreatic cancer and their possible molecular regulatory mechanisms.
Methods Based on the mRNA-Seq data of obesity and pancreatic cancer from GEO and TCGA-GTEx databases, we screened four obesity signature genes using a random forest tree algorithm and analyzed their expression in pancreatic cancer, and constructed a nomogram risk prediction model and performed preliminary validation of the predictive efficiency of the model. Then the tumor immune profile of pancreatic cancer was assessed based on the CIBERSORT algorithm, and the correlation between the four obesity genes and the abundance of tumor immune cell infiltration, and immune checkpoints in pancreatic cancer was discussed.
Results The diagnostic ROC curves suggested that the four obesity genes showed good diagnostic efficacy for pancreatic cancer, hinting that they may be potential predictive targets for pancreatic cancer, and the pancreatic cancer risk prediction model based on the four obesity-related genes showed good risk prediction efficacy for pancreatic cancer in the obese population, which has good potential for clinical application. The study also found that the upregulation of COL1A2 expression may activate the PI3K/ART signaling pathway through the mediation of integrin IGTA to promote the development of pancreatic cancer, closely associated with the developm-
ent and progression of pancreatic cancer.
Conclusion The obesity signature genes CCDC80, COL1A2, DPYSL3 and BCAT1 are potential predictive targets for new pancreatic cancer in obese people, and the upregulation of COL1A2 expression may promote pancreatic cancer development by activating the PI3K/ART signaling pathway.
Quantum Dynamics Studies on Reactive Scattering of Cl with Rotationally Excited H2
Authors: Zhang Xingyu , Meng Qingyong 
Published: June 2023

Abstract
In this work, extensive multi-configurational time-dependent Hartree (MCTDH) calculations in conjugation with the neural-network (NN) fitted potential energy surface (Science, 347 (2015), 60) were launched to study quantum dynamics of the Cl atom reacting with rotationally excited H2 molecule. Due to its direct abstraction mechanism, reaction of Cl + H2 in the ground state has no clear reaction resonances, which is well reproduced by the present work. For the reaction of Cl with H2 in rotationally excited states, the reactive probabilities are enhanced due to a Polanyi-like rule for rotationally excited states. Such Polanyi-like rule can be interpreted through the similar way as for the cases of vibrationally exicted states. Moreover, distinctive resonances peaks are investigated for these cases implying a model for generating a quasi-bound rotation state. Similar to the chemical bond softening model (Science, 347 (2015), 60; Science, 368 (2020), 767) for the vibrationally excited cases, a probable model is proposed in this work. Finally, based on the present calculations this model is further discussed to show source of the quasi-bound rotation state.
JESO: Reducing Data Center Energy Consumption Based on Model Predictive Control
Authors: Yang Shu , Xu Guizhao , Chang Xiaolei , Chen Zhengjian , Dong Qingzhen , Cui Laizhong 
Published: June 2023

Abstract
With the development of the Internet, the demand for data centers is growing dramatically.
The cost of running a data center mainly comes from the huge electricity bill.
Actually, IT (Information Technology) equipment and the HVAC (Heating, Ventilation, and Air Conditioning) system of the data center consume the majority of electricity.
The existing energy--saving researches usually consider IT equipment or the HVAC system separately.
But the energy consumption of HVAC is partially correlated with the running status of IT equipment. Taking methods to optimize the energy consumption of them jointly will generate more benefits.
Therefore, we proposed JESO (Joint Energy Saving Optimization), a MPC (Model Predictive Control) -based method, to realize the joint energy-saving optimization of IT equipment and the HVAC system.
We conducted extensive experiments based on generated transmission data and the HVAC system data from two real data centers.
The experimental results demonstrated that JESO based on the joint energy-saving algorithm of IT equipment and the HVAC system can further reduce energy consumption as compared to baselines and will not negatively affect the data transmission latency of the IT equipment.
Lifted Antipodal Graviton Regularization from VEVs: Convergences plus Higgs-3-Gluons Duality
Authors: maalouf hani 
Published: June 2023

Abstract
A discrete skip operator, turning alternate to the Liouville theory, provides the link between the Higgs and 3-gluons along a non-Gaussian Regularization for the Graviton based on indices. Such is shown with factors from the Anti-podal Symmetry, plus its unambiguous renormalizable’ liftings. That resolves, their so far abstract connection, via the MHV vertices. The procedure relied on a small variation of an effective Lagrangian cosmological term constant due to the rolling fluctuations, under a scalable Gauss-Bonnet Gravity. Verified, via alternating, so convergent, expansion diagrams coefficients, containing Gluons and Higgs. Thus such sorted feature plus its correlators from high dimensional operators pin out limits and analyticity for the gravitational interactions.
Reproductive care in Thai women with diabetes mellitus: A descriptive cross-sectional study
Authors: Pothongsangarun Kritat , Li Jiayu , Naeowong Witthawat , Apirakviriya Chayanis , Phutrakool Phanupong , Juntamongkol Tunchanok , Sae-chueng Thita , Horpratraporn Kantasorn , Jaisamrarn Unnop , Santibenchakul Somsook 
Published: June 2023

Abstract
Background
Pre-existing diabetes mellitus (DM) is a challenging pregnancy complication as poor glycemic control is associated with adverse maternal and fetal outcomes. In this study, we aimed to investigate DM-related knowledge, attitudes, preconception care practices, and contraceptive prevalence in women with DM.
Methods
This descriptive cross-sectional survey was conducted among reproductive-aged Thai women receiving DM treatment at King Chulalongkorn Memorial Hospital between August 1, 2021, and June 30, 2022. Patients with DM who were not pregnant or trying to conceive and could be contacted via the phone were included and a validated self-administered questionnaire was distributed electronically.
Results
A total of 238 participants were included in the final analysis, yielding 69.4% response rates. The median (interquartile range [IQR]) score for knowledge of pregnancy planning and pregnancy-related risks was 6.0 (3.4) out of 15. Only about half of the participants had discussed pregnancy planning with their physicians. Multivariable analysis showed that younger age at DM diagnosis, married, higher education, and medical personnel were significantly associated with higher knowledge scores. Women aged > 45 and those with higher practice scores had significantly higher adjusted odds of using highly effective contraception; the most common methods included male condoms and combined oral contraceptive pills. There was an unmet need for contraception in 9.5% of women with DM.
Conclusions
Although highly effective contraception is safe for patients with DM, only about half of our participants used tier one or two contraceptives or had received consultation regarding preconception planning. There was a notable gap in care coordination among specialists; integrating reproductive healthcare into DM therapy would improve access to preconception care.
Pneumonia hospitalization risk attributable to ambient air pollution and temperature in a mid-temperate, industrial city: a time-series analysis
Authors: Xu Jiaying , Jia Huanhuan , Li Ming , Feng Tianyu , Qi Xiaodan , Yu Xihe 
Published: June 2023

Abstract
Background Pneumonia has become a public health problem of global concern, in which air pollution and meteorological conditions were important influencing factors.
Methods A time series analysis was conducted on the number of pneumonia hospitalizations. The generalized additive model and distributed lag nonlinear model were used to investigate the single-day and cumulative lag-day effects of air pollutants and temperature on pneumonia hospitalizations.
Results Air pollutants and meteorological factors were significantly associated with pneumonia hospitalizations. Over 7 days cumulative lag time, when the PM2.5, PM10, SO2, CO, and NO2 increased by 10 µg/m3(0.1 mg/m3 for CO), pneumonia hospitalizations increased by 0.56% (95% CI: 0.30, 0.81), 0.82% (95% CI: 0.62, 1.03), 4.74% (95% CI: 3.98, 5.50), 1.99% (95% CI: 1.60, 2.38), and 5.00% (95% CI: 4.24, 5.75) respectively, women and children are at higher risk. Within a cumulative lag time of 7 days, extreme cold (-18°C versus − 1°C) and extreme heat (27°C versus − 1°C) increased the risk of pneumonia hospitalizations by 8.96% (95% CI: 0.20, 18.49) and 40.78% (95% CI: 21.85, 62.65), respectively, with a higher risk in males, children, and elderly individuals.
Conclusions From 2015 to 2019, pneumonia in Changchun showed an increasing trend and decreased sharply in 2020. Increased concentrations of air pollutants (PM2.5, PM10, SO2, CO, and NO2) led to an increased risk of pneumonia hospitalizations, with a significant lag effect, among them, SO2 and NO2 are the strongest effect. Extreme heat and cold can lead to an increased risk of pneumonia hospitalizations.
Taxation policy and regulation efficiency on increasing zakat collection: countries comparison analysis
Authors: Athief Fauzul Hanif Noor , Rachman Mohammad Aulia , Rizki Darlin , Hakim Lukmanul , Mohd Noh Mohd Shahid Bin 
Published: June 2023

Purpose - This study investigated the policies over countries, specifically concerning the taxation in its regard with the zakat collection. The aim is to see whether making zakat compulsory helps solving zakat collection problem or not.Method - The study used a descriptive analysis model with a qualitative approach. The range of data collected in 2006-2017 came from nine countries, namely Saudi Arabia, Kuwait, Sudan, Jordan, Brunei Darussalam, Malaysia, Indonesia, Singapore, Pakistan.Result - The results of this study indicate that Sudan, Brunei Darussalam, Singapore and Pakistan follow a mandatory approach while Malaysia, Kuwait, Indonesia, Jordan and Saudi Arabia follow a voluntary approach. It was also found that a mandatory approach attracted more zakat collection as indicated by the zakat collection ratio.Implication - Pointing out that mandating zakat by imposing it through regulations helps collect more zakat payments.Originality - This research specifically contributes to studying the tax system in various countries to stimulate the collection of zakat by using a comparative study.
Simulation of dam-break flood and risk assessment: a case study of Chengbi River Dam in Baise, China
Authors: Mo Chongxun , Cen Weiyan , Lei Xingbi , Ban Huazhen , Ruan Yuli , Lai Shufeng , Shen Yue , Xing Zhenxiang 
Published: June 2023

Abstract
When a reservoir is damaged, it will bring destruction to people's lives and the regional economy. Flood simulation and risk assessment are two effective ways to mitigate flood risk. Flood risk is assessed by using flood hazard and vulnerability indices. However, one of the key concerns is how to quantify hazards and vulnerabilities more rationally. To this end, this study introduces a new quantitative method for flood risk assessment. Three schemes – full dam breach (S1), 1/2 dam breach (S2), and 1/3 dam breach (S3) – were proposed for flood simulation. HEC-RAS 2D was used to simulate the evolution process of dam-break floods. This study used a new quantification approach to calculate flood risk based on simulation results. The results show the following: (1) The inundation process is similar under the three schemes, but the degree differs. The greater the degree of dam break, the greater the inundation depth, maximum flow velocity, and inundation duration. (2) High-risk areas decrease with decreased dam break degree. Under the three schemes, the flood risk areas of Longjing Street account for 65.37, 71.41, and 66.22% of the total risk areas, respectively, which are the areas most affected by dam-break floods.
Effects of Dietary Flavonoids on the Metabolism of Vortioxetine and
its Potential Mechanism
Authors: Lin Yuxian , Wang Yu , Ye Zhize , Gao Nanyong , Xu Xinhao , Weng Qinghua , Xu Ren-ai , Ye Lei 
Published: June 2023

Introduction:
Quercetin and apigenin are two common dietary flavonoids widely found in
foods and fruits. Quercetin and apigenin can act as the inhibitors of CYP450 enzymes, which may affect
the pharmacokinetics of clinical drugs. Vortioxetine (VOR), approved for marketing by the Food and
Drug Administration (FDA) in 2013, is a novel clinical drug for treating major depressive disorder
(MDD).

Objective:
This study aimed to evaluate the effects of quercetin and apigenin on the metabolism of VOR
in in vivo and in vitro experiments.

Method:
Firstly, 18 Sprague-Dawley rats were randomly divided into three groups: control group
(VOR), group A (VOR + 30 mg/kg quercetin) and group B (VOR + 20 mg/kg apigenin). We collected the
blood samples at different time points before and after the final oral administration of 2 mg/kg VOR. Subsequently,
we further used rat liver microsomes (RLMs) to investigate the half-maximal inhibitory concentration
(IC50) of the metabolism of vortioxetine. Finally, we evaluated the inhibitory mechanism of two
dietary flavonoids on VOR metabolism in RLMs.

Results:
In animal experiments, we found AUC (0-∞) (area under the curve from 0 to infinity) and CLz/F
(clearance) to be obviously changed. Compared to controls, AUC (0-∞) of VOR in group A and group B
was 2.22 and 3.54 times higher, respectively, while CLz/F of VOR in group A and group B was significantly
decreased down to nearly two-fifth and one-third. In in vitro studies, the IC50 value of quercetin and
apigenin in the metabolic rate of vortioxetine was 5.323 μM and 3.319 μM, respectively. Ki value of
quercetin and apigenin was found to be 0.040 and 3.286, respectively, and the αKi value of quercetin and
apigenin was 0.170 and 2.876 μM, respectively.

Conclusion:
Quercetin and apigenin exhibited inhibitory effects on the metabolism of vortioxetine in vivo
and in vitro. Moreover, quercetin and apigenin had a mixed mechanism on the metabolism of VOR in
RLMs. Thus, we should pay more attention to the combination between these dietary flavonoids and VOR
in the future clinical use.
Automating Drug Discovery using Machine Learning
Authors: Abdul Raheem Ali K. , Dhannoon Ban N. 
Published: June 2023

Abstract:
Drug discovery and development have been sped up because of the advances in computational
science. In both industry and academics, artificial intelligence (AI) has been widely used. Machine
learning (ML), an important component of AI, has been used in a variety of domains, including
data production and analytics. One area that stands to gain significantly from this achievement of machine
learning is drug discovery. The process of bringing a new drug to market is complicated and
time-consuming. Traditional drug research takes a long time, costs a lot of money, and has a high failure
rate. Scientists test millions of compounds, but only a small number make it to preclinical or clinical
testing. It is crucial to embrace innovation, especially automated technologies, to lessen the complexity
involved in drug research and avoid the high cost and lengthy process of bringing a medicine
to the market. A rapidly developing field, a branch of artificial intelligence called machine learning
(ML), is being used by numerous pharmaceutical businesses. Automating repetitive data processing
and analysis processes can be achieved by incorporating ML methods into the drug development process.
ML techniques can be used at numerous stages of the drug discovery process. In this study, we
will discuss the steps of drug discovery and methods of machine learning that can be applied in these
steps, as well as give an overview of each of the research works in this field.
Predicting Intention for Food Safety Behavior among Food Handlers:
A Cross-sectional Study in Indonesia’s Beach Culinary Area
Authors: Rustiawan Asep , Sulaeman Endang Sutisna , Suminah Suminah , Mulyani Sri 
Published: June 2023

Background:
The food safety behavior of food handlers constitutes the main factor in
foodborne disease control. According to the Theory of Planned Behavior, behavior is determined by
the intention that is established from a combination of attitudes, subjective norms, and perceived
behavioral control. This research aimed to predict the intention for food safety behavior using the
Theory of Planned Behavior.

Methods:
A cross-sectional study was conducted for two months in the Bantul beach culinary area,
Yogyakarta, Indonesia. The research population consisted of 80 food handlers representative of all
existing seafood stalls. The respondents were interviewed face-to-face using a paper-based questionnaire
related to attitudes, subjective norms, perceived behavioral control, and intention. The data
collected were evaluated using structural equation model-partial least square (SEM-PLS), version
3.0, with a sig. level of 0.05.

Results:
This research successfully predicted 64.3% of the variance in the intention for food safety
behavior of food handlers (R2 adjusted = 0.643). The variable-perceived behavioral control was the
strongest and most significant predictor, with a positive effect on intention for food safety behavior
(β = 0.560, p = 0.000 < 0.05), followed by the variable subjective norms (β = 0.275, p = 0.001 <
0.05). The variable attitude was the weakest predictor, with an insignificant positive effect (β =
007.0, p = 0.182 > 0.05).

Conclusion:
This research successfully predicted the intention for food safety behavior of food
handlers in the Bantul beach culinary area, Yogyakarta, Indonesia.