bluuebunny/crossref_metadata_2025_split huggingface dataset:
Full Mouth Rehabilitation of A Child with Early Childhood Caries: A Case Report
Authors: Saharia Nancy Priya , Mathur Shivani , Verma Urvashi , - Priyanka 
Published: July 2023

Early childhood caries is a multifactorial disease that severely degrades the primary maxillary incisors and molars in a child aged 71 months or younger. It can cause reduced masticatory efficiency, loss of vertical dimension, development of speech problems, esthetic-functional problems such as malocclusion and space loss, and psychological problems that can compromise the behavioral development of the child. The treatment of severely decayed primary teeth presents a special challenge to pediatric dentists. The present case report describes the oral rehabilitation of a 5-year-old male patient with type II ECC whose teeth were restored using various treatment modalities including preformed space maintainers, preformed zirconia crowns, fiber post, SSC, pulpectomies and composite restorations.
Keywords: Early Childhood Caries, Stainless-steel crowns, Zirconia crowns, Fibre-post, Dental caries
The development of simultaneous transducer ultrasonic with dual-transducer to measure flow velocity in the pipe
Authors: Wiranata Lalu Febrian , Kurniadi Deddy 
Published: July 2023

There are still several obstacles to calculating fluid flow rate measurement on custody transfer, such as the distribution of one-phase fluid flow rate, less sTable pressure, and fluid flow rate changes, which are still the main problems in the process of a measuring system. To calculate the flow rate of one phase fluid, there is a method often used, namely transit time. In practice, the transit time works to send the ultrasonic pulse from upstream to downstream, which had to have a delay because the transducer must switch the function of a transducer to become transmitter or receiver. So, this paper proposed a new strategy of measurement multipath ultrasonic flowmeter (UFLW) with a simultaneous transit time method using a dual transmitter and receiver. The simultaneous method is a measuring technique that utilizes a pair of ultrasonic transducers as both trigger and receiver. The first transducer serves as the transmitter, while the second functions as the receiver, capturing the signal at the same time without changing their positions or roles. In order to implement the configuration setup, let’s try to use 3 paths configuration with 6 pairs of transducers, 3 on the upstream and 3 on the downstream. To estimate the flow velocity, let’s use long short-term memory (LSTM), which is one of the recurrent neural networks (RNN) architectures in the deep learning algorithm, and to evaluate the performance, let’s use the Bland-Altman plot and root mean squared error (RMSE) and validation loss of the LSTM model. The result shows RMSE 0.289 from the actual flow velocity, which means an LTSM with simultaneous multipath ultrasonic can reduce the error between prediction and actual measurement
Comparison of queen honey bee colony migration with various MPPTs on photovoltaic system under shaded conditions
Authors: Aripriharta Aripriharta , Bayuanggara Triawan Waskita , Fadlika Irham , Sujito Sujito , Afandi Arif Nur , Mufti Nandang , Diantoro Markus , Horng Gwo-Jiun 
Published: July 2023

Shaded conditions cause a decrease in the performance of photovoltaic (PV) systems. In this situation, the power versus voltage curve shows two maximum power points, namely local (LMPP) and global (GMPP). The main challenge for extracting the maximum power from a PV system during shading conditions is the existence of a false maximum or LMPP along with a true maximum or GMPP. Traditional maximum power point tracking (MPPT) has faced hurdles in overcoming the situation. Therefore, this paper describes the implementation of Queen Honey Bee Migration (or QHBM for short) to track GMPP of PV systems, which called QHBM MPPT. The highlight of this paper is the simulation results of QHBM MPPT on PV systems under various shading conditions.
We implemented QHBM MPPT on a boost converter installed on a 1200 Wp PV system. We conducted a simulation using MATLAB® with five scenarios which aim to show the various shadows that PV systems might encounter in reality. The MPPT QHBM is tested repeatedly and then the average value is taken to measure performance in MPP tracking. The average value is used to calculate tracking efficiency, number of iteration or convergence time. We also compared QHBM with other methods, namely incremental conductance (IC) and Particle Swarm Optimization (PSO). The results obtained show that the QHBM and PSO MPPTs outperform the IC MPPT in terms of efficiency, convergence time and the number of iterations. IC MPPTs oscillate under shading conditions since no knowledge of GMPP. Both PSO and QHBM MPPTs know GMPP from scouts or particles, respectively. Therefore, PSO and QHBM MPPTs are better than IC MPPT in various shading cases
Influence of a combined interferon-alpha-containing drug on the course of respiratory diseases in frequently ill children
Authors: Zakirova A. M. , Moroz T. B. , Shayapova D. T. , Kadriev A. G. , Palmova L. Yu. , Rashitova E. L. , Zotova A. E. , Khairullina L. A. , Kiselev R. P. , Kadriev D. A. 
Published: July 2023

Introduction. Acute respiratory viral infections hold a dominant place in the infectious diseases pattern. There are many drugs that can affect separate arms of the immune response.Aim. To analyze the effectiveness of the systemic use of a combined drug containing interferon-α-2b and a complex immunoglobulin preparation in the treatment of respiratory diseases in frequently ill children.Material and methods. We examined 103 children aged 2-12 years. Upon admission, the children were treated with a combined drug containing interferon a-2b and a complex immunoglobulin preparation (CIP) (Kipferon®) rectally. Children in the control group received standard therapy.Results. Children were admitted to the hospital in the first days of the disease (66.02%), mainly in the moderate form of the disease (96.12%). 81.55% had symptoms of intoxication, catarrhal phenomena and respiratory syndrome. Comparing the time from the onset of the disease when prescribing IFN-α-2b to children, their significantly significant differences were established. Introduction in the early stages of the disease contributes to a faster elimination of all symptoms: fever stopped on average (M ± SD) after 1.76 ± 0.33 and 2.05 ± 0.29 days, respectively, from the moment of admission to the hospital, which was on average 2 days less than in the control group. The transition to a productive cough in the main group occurred on average (M ± SD) after 3.25 ± 0.27 days, in the comparative group - after 5.23 ± 0.31, in the control group - after 8.19 ± 0.42 days. In patients of the main and comparative groups, the length of stay in the hospital was significantly shorter - on average (M ± SD) 8.04 ± 0.81 days than in the control group - 10.56 ± 1.42 days. Hematological parameters returned to normal at an earlier time.Discussion. Rectal route of recombinant IFNi-a2b delivery as suppositories is substantiated with regard to etiopathogenesis and immunology.Conclusion. The article presents the outcomes of the clinical use of Kipferon® as part of the combination therapy and prevention of complications of acute respiratory viral infections in children: reduced duration of intoxication, fever, faster improvement of the auscultatory status of the lungs, improvement of immune status indicators.
Glycemic control in children receiving glucocorticoid therapy
Authors: Vitebskaya A. V. , Popovich A. V. , Afonina E. Yu. , Batyreva O. V. 
Published: July 2023

Hyperglycemia is a well-known side effect of glucocorticoid (GC) therapy. GC treatment can lead to steroid diabetes mellitus (DM) manifestation. Glycemic control is essential for patients receiving GC. Three clinical cases of carbohydrate metabolism impairment (hyperglycemia) in children receiving GC needing glycemic control were described. In the 1st case transient fasting hyperglycemia up to 8.3 mmol/l (while normal data after meals) was detected during 3 days after start of GC pulse-therapy of bronchial asthma. Normalization of glycaemia was evident since the 4th day in spite of GC therapy continuing for 6 days. In the 2nd case transient hyperglycemia while pulse-therapy of juvenile arthritis with systemic onset was detected on the 3rd day (7.25 mmol/l), GC in tablets was added, pulse-therapy with gradually dose reduction continued 9 days else. Hyperglycemia (up to 11.7 mmol/l) persisted for 4 days, then glycaemia normalization was detected in spite of continuing GC therapy (50 mg or 0.7 mg/kg). In the 3rd case steroid DM in a patient with juvenile systemic scleroderma, familial history of DM type 2, and obesity manifested after 2 months of treatment with GC tablets (35 mg or 0.6 mg/kg), metformin was prescribed. While reduction of GC dose trend to glycaemia normalization was seen. In 4 months after cessation of GC impaired glucose tolerance and insulin resistance were diagnosed.Glycemic control is essential for patients receiving GC. Hyperglycemia while receiving GC can be both transient or persistent. Risk of steroid DM is higher in cases of family history of DM type 2, obesity, high doses, and prolonged GC treatment. In patients at-risk of DM type 2 impairment of carbohydrate metabolism can persist after cessation of GC; this needs repeated examination.
Water affordability analysis: a critical literature review
Authors: Fagundes Thalita Salgado , Marques Rui Cunha , Malheiros Tadeu 
Published: July 2023

Abstract
Water and sanitation affordability has drawn researchers’ attention over the past years due to the recent economic crisis and the growing role of tariffs on funding services. This paper conducted a systematic review of previous research on water and/or sanitation affordability and a critical qualitative discussion on the methodologies adopted. The research framework relied on a hybrid approach that combines systematic quantitative and narrative analyses. The literature review protocol applied returned 79 relevant studies published by journals and recognized international organizations and four key topics, namely affordability indicators, threshold, data source, and practical use of the analysis were identified and critically discussed. This paper contributes to the literature by presenting and discussing the most important water affordability issues and enlightening the potential role of the analysis in public financial policies.
Predictive uncertainty assessment in flood forecasting using quantile regression
Authors: M. K. Amina , N. R Chithra 
Published: July 2023

Abstract

Floods and their associated impacts are topics of concern in land development planning and management, which call for efficient flood forecasting and warning systems. The performance of flood warning systems is affected by uncertainty in water level forecasts, which is due to their inability to measure or calculate a modeled value accurately. Predictive uncertainty is an emerging type of uncertainty modeling technique that emphasizes total uncertainty quantified as a probability distribution conditioned on all available knowledge. Predictive uncertainty analysis was done using quantile regression (QR) for machine learning-based flood models – Hybrid Wavelet Artificial Neural Network model (WANN) and Hybrid Wavelet Support Vector Machine model (WSVM) for different lead times. Comparing QR models of WANN and WSVM revealed that the slope, intercept, spread of forecast, and width of confidence band of the WANN model are more for each quantile indicating more uncertainty as compared to the WSVM model. In both models, with an increase in lead time, uncertainty has shown an increasing trend as well. The performance evaluation of inference obtained from QR models was evaluated using uncertainty statistics such as prediction interval coverage probability, average relative interval length (ARIL), and mean prediction interval (MPI).
Rainfall prediction in coastal hilly areas based on VMD–RSA–DNC
Authors: Zhang Xianqi , Yin Qiuwen , Liu Fang , Li Haiyang , Chen Haiyang 
Published: July 2023

Abstract

Highly accurate rainfall prediction can provide a reliable scientific basis for human production and life. For the characteristics of occasional and sudden changes of rainfall in coastal hilly areas, this article chooses four cities in the eastern Zhejiang province as the object of the study and establishes a rainfall prediction model based on variational mode decomposition (VMD), reptile search algorithm (RSA), and differentiable neural computer (DNC). The VMD algorithm reduces the complexity of the sequence data; RSA is used to find the best-fit function; and DNC combines the advantages of the recurrent neural network and computational processing to improve the problem of memory forgetting of long short-term memory. To verify the prediction accuracy of the model, the prediction results are compared with the other three models, and the results show that the VMD–RSA–DNC model has the best prediction with the maximum and minimum relative errors of 9.62 and 0.17%, respectively, the average root-mean-square error of 5.43, the average mean absolute percentage error of 3.59%, and the average Nash–Sutcliffe efficiency of 0.95 for predicting four cities in the coastal hilly area. This study provides a new reference method for the construction of rainfall prediction models.
Temporal and spatial estimation of groundwater electrical conductivity using soft computing approaches: Analysis of East Azerbaijan Province, Iran
Authors: Zamanzad-Ghavidel Sarvin , Sobhani Reza , Fazeli Sina , Noto Leonardo Valerio , De Michele Carlo , Pumo Dario 
Published: July 2023

Abstract

The evaluation of groundwater quality plays an important role in the management of groundwater. The main objectives of the present work are to develop a novel soft computing framework including Adaptive Neuro-Fuzzy Inference System (ANFIS), Wavelet-ANFIS (WANFIS), Gene Expression Programming (GEP), and Wavelet-GEP (WGEP) for the temporal and spatial estimation of groundwater electrical conductivity (EC) in the East Azerbaijan province, Iran over 2001–2020. The results demonstrate the importance of wavelet transform application; the performance percentage enhancement of the WANFIS and WGEP models compared to the ANFIS and GEP, using the RMSE criterion, ranged from 15.48 to 51.09% and from 5.06 to 86.95%, respectively. All the developed models showed the WGEP superior compared to others. The impact of land use characteristics, climatic conditions, and geological features on groundwater quality showed that there is a direct relationship between the extent of agricultural land, semi-arid climate conditions and groundwater EC amounts. The results demonstrated that the values of EC increase from east to west, indicating the direct exchange of surface and groundwater in the study area. Moreover, groundwater quality changes significantly across the width of the fault, with groundwater EC in the northern part of the fault higher than that in the southern part.
Removal of Cr(VI) ions from wastewater by Fe3O4-loaded porous sludge biochar
Authors: Yu Chaoyang , Liao Yuliang 
Published: July 2023

Abstract

In this work, porous sludge biochar (PSBC) was prepared by molten salt-assisted pyrolysis of municipal sludge, and PSBC loaded with Fe3O4 (Fe3O4@PSBC) was synthesized by chemical precipitation. The effects of pH (2.0–10.0), sorbent dosage (0.1–2 g/L), coexisting ions (Ca2+, Mg2+, Cu2+, Pb2+, Cl–, SiO32-, NO3-, CO32-, SO42-, and PO43-), adsorption temperature (288, 298, and 308 K), initial Cr(VI) ion concentrations (50–150 mg/L), and adsorption time (5–300 min) on the removal of Cr(VI) ions by the sorbent were investigated. The mechanism of the removal of Cr(VI) ions was characterized by scanning electron microscope (SEM), Fourier transform infrared (FTIR), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS). The result showed that the removal of Cr(VI) ions on PSBC and Fe3O4@PSBC had a strong dependence on the pH of solution. The maximum adsorption capacity of Cr(VI) ions by PSBC and Fe3O4@PSBC was 162 and 209 mg/g, respectively, at a dosage of 0.4 g/L, pH of 3, and temperature of 298 K. The removal process of Cr(VI) ions could be fitted by the Langmuir isotherm model and pseudo-second-order kinetic model. The breakthrough curves were in good agreement with the theoretical values of the Thomas model. The mechanism of the removal of Cr(VI) ions by Fe3O4@PSBC mainly contain complexation, reduction, and electrostatic interaction. This work proposes a new removal material for Cr(VI)-containing wastewater.
Automated Brain Tumor Detection using Ideal Shallow Neural Network with
Artificial Jellyfish Optimization
Authors: Sridhar Salem Rajagopalan , Akila Muthuramalingam , Asokan Ramasamy 
Published: July 2023

Introduction:
Brain tumors are predicted from Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) scan images. In recent years, image
processing-based automated tools are developed to predict tumor areas with less human interference. However, such automated tools are suffering
from computational complexity and reduced accuracy in certain critical images. In the proposed work, an Ideal Shallow Neural Network (ISNN) is
utilized to improve the prediction accuracy, and the computational complexity is reduced by implementing an Artificial Jellyfish Optimization
(AJO) algorithm for minimizing the feature dimensionality.

Methods::
The proposed method utilizes MRI images for the verification process as they are more informative than the CT scan image. The BRATS and the
Kaggle datasets are used in this work and a Gabor filtering technique is used for noise reduction and a histogram equalization is used for enhancing
the tumor boundary regions. The classification results observed from the AJO-ISNN are further forwarded towards the segmentation process and
which uses the Centroid Weighted Segmentation (WCS) along with a Grasshopper Optimization Algorithm (GOA) for improving the segmentation
over the boundary regions of the brain tumor.

Results::
The experimental result indicates a classification accuracy of 95.14% on the proposed AJO-ISNN model and AJO-ISNN is comparatively better
than the Convolutional Neural Network (CNN) model accuracy of 85.41% and VGG 19 model accuracy of 93.75% while implemented with the
AJO optimization model. Similarly, the Dice Similarity Coefficient of the proposed CWS-GOA also reaches 93.15% when performed with both
BRATS and Kaggle datasets.

Conclusion::
Apart from the accuracy attainments the proposed work classifies and segments the tumor region in around 65 seconds on average of 200 image
verifications and that is comparatively better than the previous multi-cascaded CNN and the InceptionV3 models.
Analysis of Research Publications on Leprosy Drugs Related Adverse
Drug Reactions – A Scinetometric Study
Authors: Thangaraju Pugazhenthan , Chandu Himanshu Nirmal , Velmurugan Hemasri , Venkatesan Sajitha 
Published: July 2023

Abstract:
Leprosy is curable and can be treated with multidrug therapy in the early stages. As a result,
we chose a Scientometrics evaluation of leprosy research guides on adverse drug reactions to better
grasp the current popularity of drug-related responses. During the 2010-2021 a study with a total of 48
publications was selected. This study aims to analyze scientometric tools such as frequency distribution,
percentage analysis, double-related growth rate, and interaction rate. During the study period, 7
(14.58%) study publications were submitted in 2018. The related growth rate is identified by decreasing
trend and the double time is growing from 2010 to 2021. The 11 published study sizes (22.92%)
were provided by top writers, the average Degree of Collaboration is 0.96, and 19 (39.58%) published
research articles by headers. India is the largest supplier of 21 leprosy research publications (43.75%).
As India is the most productive country in leprosy research, hence there are four out of the top five institutions
that are from the Indian center that is listed among the most productive institutions.
An Explainable Multichannel Model for COVID-19 Time Series Prediction
Authors: He Hongjian , Xie Jiang , Lu Xinwei , Huang Dingkai , Zhang Wenjun 
Published: July 2023

Introduction:
The COVID-19 pandemic has affected every country and changed people's
lives. Accurate prediction of COVID-19 trends can help prevent the further spread of the outbreak.
However, the changing environment affects the COVID-19 prediction performance, and previous models
are limited in practical applications.

Methods:
An explainable multichannel deep learning model with spatial, temporal and environmental
channels for time series prediction, STE-COVIDNet, was proposed. The time series data of COVID-19
infection, weather, in-state population mobility, and vaccination were collected from May, 2020, to October,
2021, in the USA. In the environmental channel of STE-COVIDNet, an attention mechanism was
applied to extract significant environmental factors related to the spread of COVID-19. In addition, the
attention weights of these factors were analyzed with the actual situation.

Results:
STE-COVIDNet was found to be superior to other advanced prediction models of COVID-19
infection cases. The analysis results of attention weight were reported to be consistent with existing
studies and reports. It was found that the same environmental factors that influence the spread of
COVID-19 can vary across time and region, which explains why findings of previous studies on the relationship
between the environment and COVID-19 vary by region and time.

Conclusion:
STE-COVIDNet is an explainable model that can adapt to environmental changes and thus
improve predictive performance.
Marine Bioactive Phytoconstituents in Autoimmune Disorders: Role and
Mechanism - A Review
Authors: Meenakshi Dhanalekshmi Unnikrishnan , Narde Gurpreet Kaur , Siddiqui Sameera , Ahuja Alka 
Published: July 2023

Abstract:
The significance of Autoimmune Disorders (Ads) is underscored by their chronic nature, high maintenance costs, and complexity affecting numerous organs and tissues. A more comprehensive approach to treating Ads is required across patient populations. A revo-lutionary area for obtaining an integrated therapeutic option is natural phytoconstituents. Di-verse biomolecules with promising properties can be found in abundance in the marine envi-ronment. Many substances have been identified from sponges, bacteria, fungi, cyanobacteria, and algae that have been shown to have immunomodulatory activities and may be used as possible treatments for Ads. Marine-derived bioactive substances have been demonstrated to affect immunological responses and to be essential in immunotherapies. The amount of in-formation about the specific effects of substances obtained from marine sources utilized as di-etary supplements or for treating immune-related diseases is growing. This paper discusses many sources of potential marine metabolic chemicals, such as maritime flora and fauna. Nu-merous marine phytoconstituents have recently been isolated, described, and identified, and they are currently undergoing human usage studies. We have attempted to consolidate infor-mation concerning phytoconstituents from marine sources with anti-inflammatory and im-munomodulatory properties in this review, and we have briefly explored their methods of ac-tion. In order to provide a baseline of knowledge for promoting marine flora-based phytocon-stituents in the current context of increasing Ads incidence, deprived of the more affordable, safe, and effective medications to combat the terrible human disease, this paper reviews the works thus far conducted on this aspect.