bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genome-Wide Identification and Codon Bias of NBS-LRR Gene Family in Banana
Authors: Fang Hui , Yu Shenxin , Li Min , Sun Jiaman , Mo Bin 
Published: August 2023

Abstract
As the largest family of plant resistance (R) proteins, nucleotide binding site-leucine-rich repeat ( NBS-LRR ) proteins play an important role in pathogen defense. In order to identify and get the codon usage bias of NBS-LRR gene family in banana. Using software MEGA11, TBtools and CodonW to analyze the codon preference and its influencing factors on genome-wide data from banana. The 74 NBS-LRR genes were divided into 6 subfamilies, 5 conserved motifs and 14 domains were identified. The more similar domain structures in the same phylogenetic tree subfamily and less consistent structures between different subfamilies. It was also found that when the G/C base appears at the third position of the codon, it had a higher usage rate. We identified 16 codons, including UCC and CCC, as the optimal codons. All of the 16 optimal codons ended with G or C, which indicated that the banana genome NBS-LRR gene prefers to use G or C terminated codons. Most of the gene points in the GC3s-ENC distribution map fell near the expected curve, mutation and natural selection during gene expression affected codon selection. The results of PR2-plot showed that most of the genes fell on the upper right side of the plane, and neutrality plot result showed that there was not significant correlation between C12 and GC3, which indicated the main factor of codon preference was natural selection. The results provide scientific basis for codon optimization of exogenous genes and improvement of their expression efficiency.
Asynchronous Domain Dynamics and Equilibration in Layered Oxide Battery Cathode
Authors: Liu Yijin , Xue Zhichen , Sharma Nikhil , Wu Feixiang , Pianetta Piero , Lin Feng , Li Luxi , Zhao Kejie 
Published: August 2023

Abstract
To improve lithium-ion battery technology, it is essential to probe and comprehend the microscopic dynamic processes that occur in a real-world composite electrode under operating conditions. The primary and secondary particles are the structural building blocks of battery cathode electrodes. Their dynamic inconsistency has profound but not well-understood impacts. In this research, we combine operando coherent multi-crystal X-ray diffraction and optical microscopy to examine the chemical dynamics in local domains of layered oxide cathode. Our results not only pinpoint the asynchronicity of the lithium (de)intercalation at the sub-particle level, but also reveal sophisticated diffusion kinetics and reaction patterns, involving various localized processes, e.g., chemical onset, reaction front propagation, domains equilibration, and non-rigid deformation. These observations shed new lights onto the activation and degradation mechanisms of state-of-the-art battery cathode materials.
Understanding the light induced hydrophilicity of metal-oxide thin films
Authors: Taboryski Rafael , Deshpande Rucha Anil , Navne Jesper , Adelmark Mathias Vadmand , Shkondin Evgeniy , Crovetto Andrea , Hansen Ole , Bachmann Julien 
Published: August 2023

Abstract
Photocatalytic effects resulting in water splitting, reduction of carbon dioxide to fuels using solar energy, decomposition of organic compounds, and light-induced hydrophilicity observed on surfaces of various metal oxides (MOx), all rely on the same basic physical mechanisms, and have attracted huge interest over the past decades. TiO2 and ZnO, two natively n-type doped wide bandgap semiconductors exhibit the effects mentioned above. In this study we propose a model for the photo-induced hydrophilicity in MOx films, and we test the model for TiO2/Si and ZnO/Si heterojunctions. Experimentally, we employ a wet exposure technique whereby the MOx surface is exposed to UV light while a water droplet is sitting on the surface, which allows for a continuous recording of contact angles during illumination. The proposed model and the experimental techniques allow a determination of minority carrier diffusion lengths by contact angle measurements and suggest design rules for materials exhibiting photocatalytic hydrophilicity. We expect that this methodology can be extended to improve our physical understanding of other photocatalytic surface effects.
Intranasal cyst marsupialization under otoscopy for congenital dacryocystocele
Authors: MD  , MD  , MD  , MD  , MD  , MD  
Published: August 2023

Abstract

Aim
We present a new, simple intranasal cyst marsupialization (ICM) technique for congenital dacryocystocele (CDC). In this procedure, the otoscope and myringotome are used to perform ICM in the manner of otoscopic myringotomy. This method allows minimally invasive surgery as an office procedure without the need for general anesthesia or a nasal endoscope.
Design:
Prospective observational study
Materials and Methods
Twenty consecutive infants with 25 CDCs administrated at our facility from 2011 to July 2023 were enrolled. Five infants with 5 CDCs required surgical interventions due to resistance to conservative treatment. Among them, we evaluated the surgical method and the outcomes of 3 infants with 3 CDCs who underwent ICM in the manner of otoscopic myringotomy.
Results
Of the total 25 CDCs, 20 (80%) spontaneously resolved with conservative treatment. Surgical intervention was conducted on five infants with 5 CDCs. The median age at surgery was 97 days with interquartile range 6–164.5 days. Surgical procedures involved one of the following methods. (1) Probing by an ophthalmologist (2 infants with 2 CDCs), (2) ICM in the inferior meatus with a myringotome and alligator forceps under otoscopy by an otolaryngologist (3 infants with 3 CDCs). All cases were treated under topical anesthesia in the office setting, with successful outcomes by a single surgical procedure.
Conclusion
CDC was successfully treated by ICM in the manner of otoscopic myringotomy. Treatment of CDC using an otoscope and myringotome is a minimally invasive surgical procedure that can be performed in the office setting without the need for general anesthesia or advanced medical equipment such as a nasal endoscope. Moreover, the risk of false passage formation and/or recurrence due to probing can be avoided. We, therefore, propose this procedure as one of the practical ICM techniques for CDC.
Impact of nurse-led intervention on asthma control among children with uncontrolled asthma, a randomized control trial study control asthma, a randomized control trial study
Authors: Hussain Altaf , - Badil , Arif Fehmina , Hussain Mehwish , Farooqi Waqas Ahmed , Hameed Faiza 
Published: August 2023

Abstract
Background and Aim:
Asthma is a chronic inflammatory disease primarily most common prevalent in children. The prevalence is high in low-income and middle-income countries, and asthma is estimated at 1 to 18% worldwide. Asthma increases health costs for patients and families, and poor asthma control increases mortality and morbidity. This study aimed to determine the effect of nursing educational intervention on asthma control in children.
Method
This randomized control trial (RCT) design study was employed among children with uncontrolled asthma aged 6 to 11 years who visited the paediatric OPD and emergency department at Dr. Ruth KM Pfau Civil Hospital Karachi. The experimental group received a nursing educational intervention session, while the control group received standard treatment. The participants' childhood asthma control test (C-ACT) score was measured before the intervention, and the post-C-ACT score measurement was made after 4 weeks using the same questionnaires and C-ACT tool.
Results
In the experimental group, the C-ACT mean score significantly improved (p < 0.05) from the pre-session (14.6 ± 2.4) to the post-session (17.5 ± 2.1). There was no significance (p = 0.76) observed in the control group C-ACT mean scores pre-intervention (15.9 ± 1.98) and post-intervention (16.0 ± 1.8).
Conclusion
A nursing educational intervention to prevent asthma triggers helped improve asthma control in children visiting the outpatient and emergency departments.
Trial registration:
Clinical Trial registered on clinicaltrial.gov (NCT number) NCT05855512, 03/05/2023 (prospectively registered).
Society, Cost of Migrants, and Digital Economy impact on Unemployment of Omani Youth’s: An Empirical investigation of The Gender Moderate Role
Authors: Abdelfattah Fadi , Balushi Nabeela Imam Bakhsh AL , Alawi Abrar Mohammed AL , Sabie Shrooq Gabish AL , Ghafri Mathael Awad AL , Alwashahi Maryam Ahmed 
Published: August 2023

Abstract

This study aims to shed light on the situation of unemployment in the Sultanate of Oman in the context of the global and national economic shift toward digital technology. In this study, the topic of youth unemployment was examined from a variety of angles, such as social perception, the cost of migrants, and the effect of the digital economy on employment opportunities. The mild impact of gender on the variables under investigation is also examined in this research. The study has applied the quantitative approach. The data was collected from Omani youths through the adopted questionnaire. A total of 312 responses were received for further analysis SPSS and Partial Least Squares (PLS) were used to analyse the data. This study demonstrated how social perception has a significant impact on Omani youth. Youth unemployment is also strongly impacted by the cost of migrant labor. As well as, the digital economy is significantly influencing youth employment opportunities. On the other hand, the association between social perception and unemployment among Omani youth is considerably influenced by the mild effect of gender. This study contributes significantly to the current knowledge of the factors influencing unemployment in the Sultanate of Oman. The research models may also be used to establish new initiatives, develop programs, and establish policies on the labour market to reduce the unemployment rate among the youth of the Sultanate of Oman.
Velocity oscillations in CME and related shock: a comparative analysis
Authors: Fainshtein Victor , Egorov Yaroslav 
Published: August 2023

Abstract
A number of studies have concluded that the velocity of coronal mass ejections (CME) does not change monotonically with time, but exhibits oscillations. They analysed moving CMEs with oscillation-averaged velocities varying within a wide range. Investigations in the past several years identified the CME boundary positions relying on data in various CME catalogues providing the positions of the most remote and, generally, fastest part of the CME boundary. No attention was paid, however, to the fact that, for fast enough CMEs, the outer part of the structure observed in the coronagraph field of view and defined as a `CME' in the catalogues, is indeed the CME-related shock. Unlike the previous investigations into the velocity oscillations of a CME moving in a coronagraph field of view, we examined the velocity oscillations of a CME (i.e. its body) separately from the velocity of the CME-related shock, for relatively fast CMEs. The characteristics of the two structures have been found to differ noticeably.
A multi-fidelity data-driven model for highly accurate and computationally efficient modelling of short fiber composites
Authors: Mirkhalaf Mohsen , Cheung Hon Lam 
Published: August 2023

Abstract
To develop physics-based models and establish a structure-property relationship for short fiber composites, there are a wide range of micro-structural properties to be considered. To achieve a high accuracy, high-fidelity full-field simulations are required. These simulations are computationally very expensive, and any single analysis could potentially take days to finish. A solution for this issue is to develop surrogate models using artificial neural networks. However, generating a high-fidelity data set requires a huge amount of time. To solve this problem, we used a developed recurrent neural network model trained on low-fidelity mean-field data, and applied transfer learning using a limited amount of high-fidelity full-field simulations. The enhanced RNN model has a very high accuracy in comparison with full-field simulations, and gives predictions in less than one second. This model can be used not only for highly efficient modeling purposes, but also for designing new short fiber composites.
Associations between Household Characteristics and Mosquito Bed Net Utilisation among Under-Five Children in Africa: A Critical Focus on Household Size, Sleeping Rooms, and Demographic Characteristics of Household Heads
Authors: Wuresah Israel , Boadi Caleb , Bonsu Emmanuel Osei , Adu Benjamin , Addo Isaac Yeboah 
Published: August 2023

Abstract
Background: Research has shown that the use of insecticide-treated nets (ITNs) reduces malaria incidence and mortality. Despite the relatively high ownership of ITNs and the substantial presence of malaria-causing agents in sub-Saharan Africa (SSA), considerable empirical evidence points to a significant underutilisation of ITNs in the region.
Objective: This study examines the influence of household characteristics (Household Size, Sleeping Rooms, and Demographic characteristics of Household Heads) on the use of ITNs among children under five years of age (under-five children) in five sub-Saharan African (SSA) countries.
Methods: This quantitative cross-sectional investigation employed data extracted from the Malaria Indicator Survey (MIS) encompassing five SSA countries, namely Ghana, Nigeria, Niger, Senegal, and Mali. The study sample comprised 59,005 participants, weighted for representativeness. The analytical procedures included descriptive statistics and multivariate logistic regression modelling, with the intent of elucidating household determinants impacting the utilisation of ITNs.
Results: Among the total of 59,005 weighted participants, the aggregate use of ITNs was 37.7%. Larger households (10+ members) (Adjusted OR=0.710; CI: 0.52, 0.98; p=0.035) had less likelihood of using ITNs for under-five children whereas households with 10+ sleeping rooms (Adjusted OR=2.37; CI: 1.11, 5.05; p=0.025) had higher odds of using ITNs for under-five children. The age, gender, and marital status of household heads did not show any statistically significant associations with ITN utilisation among the under-five children. Maternal education played a vital role, with primary (Adjusted OR=0.805; CI: 0.73, 0.89; p<0.001) and secondary education (Adjusted OR = 0.761; CI: 0.70, 0.82; p<0.001) significantly linked to lower ITN usage.
Conclusions: This study indicates that disparities in household characteristics significantly shape patterns of ITN utilisation. Focused interventions could be implemented to enhance malaria prevention strategies and overall public health results in the selected countries.
Maximizing result of bedsore prevention in mechanical ventilated patient
Authors: Ghafri Abeer Al , Ghafri Asad Al , Shuhoumi Mohammed Al 
Published: August 2023

Abstract
Objectives According to the Clinical Practice Guideline (CPG), there are several preventive interventions for Pressure ulcers, including a thorough initial examination during admission to identify risk factors, education about PUs, repositioning, and nutritional support. Hydrocolloid dressings have been used to prevent bed sores in several places, although there has not been much research. The study sought to determine the relationship between hydrocolloid dressing and the prevention of bedsores among ventilated patients.Method an observational retrospective study that included patients on mechanical ventilators. Participants were selected from the covid ward in the Ibri hospital population. Pretest and post-test investigations were done using conventional or conventional care with preventive hydrocolloid dressing. Information was obtained from staff recordings and assessments in AlShifa 3 plus program.Result Seventy-four patients were included in the study. Forty patients were included in the pretest, using conventional care only, and 34 patients were included in the post-test, using conventional treatment and hydrocolloid dressing. A decrease in the number of occurrences of bedsores from 22 (55%) at the pretest to 5 (15%) at the post-test. Most bedsore stage occurs in the post-test was stage one (4 out of 34) and was mainly related to patients with comorbidities.Conclusion The study findings reveal a significant difference between the post-test and PUS variable of using CC + HD (p-value − 0.000 < 0.05), reducing harm to the patients. It is necessary to promote trials that lead to comparing different preventive measures.
A comparison of the performance of SWAT and artificial intelligence models for monthly rainfall–runoff analysis in the Peddavagu River Basin, India
Authors: Shekar Padala Raja , Mathew Aneesh , Pandey Arunabh , Bhosale Avadhoot 
Published: August 2023

Abstract

Rainfall–runoff (R–R) analysis is essential for sustainable water resource management. In the present study focusing on the Peddavagu River Basin, various modelling approaches were explored, including the widely used Soil and Water Assessment Tool (SWAT) model, as well as seven artificial intelligence (AI) models. The AI models consisted of seven data-driven models, namely support vector regression, artificial neural network, multiple linear regression, Extreme Gradient Boosting (XGBoost) regression, k-nearest neighbour regression, and random forest regression, along with one deep learning model called long short-term memory (LSTM). To evaluate the performance of these models, a calibration period from 1990 to 2005 and a validation period from 2006 to 2010 were considered. The evaluation metrics used were R2 (coefficient of determination) and NSE (Nash–Sutcliffe Efficiency). The study's findings revealed that all eight models yielded generally acceptable results for modelling the R–R process in the Peddavagu River Basin. Specifically, the LSTM demonstrated very good performance in simulating R–R during both the calibration period (R2 is 0.88 and NSE is 0.88) and the validation period (R2 is 0.88 and NSE is 0.85). In conclusion, the study highlighted the growing trend of adopting AI techniques, particularly the LSTM model, for R–R analysis.
Runoff time series prediction using LSTM dynamic neural network optimized by logistic chaotic mapping chicken swarm algorithm
Authors: Yang Wenyu , Li Junfeng , Gu XueGe , Qu Wenying , Ma Chengxiao , Feng Xueting 
Published: August 2023

Abstract

An algorithm, named long short-term memory (LSTM)-logistic chaos mapping chicken swarm algorithm (LCCSA), is proposed for initializing the weights and thresholds of LSTM neural networks using the Logistic chaotic mapping chicken swarm algorithm (CSA). This algorithm aims to improve mid- to long-term runoff sequence prediction in river basins. In this model, the logistic chaotic mapping method is used to initialize the chicken swarm, and LCCSA is employed to pre-train the weights and thresholds of each layer of LSTM 50 times, using the training results' initial weights of LSTM to enhance convergence accuracy and speed. Taking the Manas river and Kuitun river, two typical basins in northern Xinjiang, China, as the research objects, LSTM-LCCSA was used to forecast the mean monthly runoff in the mid- to long-term under different lag time series by using the runoff evolution data within a certain period. The example using the basin located in northern Xinjiang demonstrates the effectiveness, stability, and generality of the LSTM-LCCSA method in mid- to long-term prediction of average monthly runoff, and the prediction accuracy and universality of LSTM-LCCSA are better than other data-driven models.
Bi-LSTM and partial mutual information selection-based forecasting groundwater salinization levels
Authors: Muniappan A. , Jarin T. , Sabitha R. , Ghfar Ayman A. , Fattah I. M. Rizwanul , Bowa Chilala Kakoma , Mwanza Mabvuto 
Published: August 2023

Abstract

Fresh-saline groundwater is distributed in a highly heterogeneous way throughout the world. Groundwater salinization is a serious environmental issue that harms ecosystems and public health in coastal regions worldwide. Because of the complexities of groundwater salinization processes and the variables that influence them, it is challenging to predict groundwater salinity concentrations precisely. It compares cutting-edge machine learning (ML) algorithms for predicting groundwater salinity and identifying contributing factors. It employs bi-directional long short-term memory (BiLSTM) to indicate groundwater salinity. The input variable selection problem has attracted attention in the time series modeling community because it has been shown that information-theoretic input variable selection algorithms provide a more accurate representation of the modeled process than linear alternatives. To generate sample combinations for training multiple BiLSTM models, PMIS-selected predictors are used, and the predicted values from various BiLSTM models are also used to calculate the degree of prediction uncertainty for groundwater levels. The findings give policymakers insights for recommending groundwater salinity remediation and management strategies in the context of excessive groundwater exploitation in coastal lowland regions. To ensure sustainable groundwater management in coastal areas, it is essential to recognize the significant impact of human-caused factors on groundwater salinization.
Combination of peracetic acid dosing with diffused aeration in municipal wastewater treatment
Authors: Luukkonen Tero , Heponiemi Anne 
Published: August 2023

Abstract

Wastewater aeration is an important unit operation that provides dissolved oxygen for microorganisms in wastewater treatment. In this study, the impact of peracetic acid (PAA) dosing on wastewater aeration was assessed in terms of oxygen transfer, visual observation of bubble size changes, and evolution of dissolved oxygen from PAA (and H2O2) decomposition. Oxygen transfer coefficients improved with PAA concentrations of up to 7 mg/L, which was probably due to the smaller bubbles being formed from the aeration diffuser and evolution of small bubbles from PAA (and H2O2) decomposition. At a PAA concentration higher than 7 mg/L, the accumulation of acetate molecules to the gas–liquid interface of bubbles likely began to counteract the positive impact of bubble size decrease by increasing the mass transfer resistance of oxygen from bubbles to water. Finally, a continuous bench-scale primary effluent aeration experiment demonstrated that at a continuous PAA dosing of 1 mg/L, the air input by a compressor could be decreased by 54%, while keeping the oxygen level constant at approximately 1.5 mg/L. PAA dosing could be combined, for example, with aerated grit removal to enhance the primary effluent aeration together with additional benefits of partial disinfection and odor formation prevention.