bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multiple Molecular and Biochemical Alterations in Zebrafish Exposed to Terbuthylazine and Malathion
Authors: Khatib Ihab , Horyn Oksana , Bodnar Oksana , Rychter Piotr , Lushchak Oleh , Falfushynska Halina 
Published: January 2023

Abstract
In the context of the global increase in pesticide applications, aquatic animals are constantly subjected to their action in natural reservoirs. Our research sought to determine the molecular and biochemical effects of an environmental exposure to commonly used chloro-s-triazine herbicide terbuthylazine and organophosphate insecticide malathion on zebrafish. To this aim, mature zebrafish were exposed to 2 and 30 µg L−1 terbuthylazine and 5 and 50 µg L−1 malathion alone and in combination for 14 days. Following exposure, induction of reactive oxygen and nitrogen species, lipid peroxidation, and protein carbonylation in the liver of treated zebrafish have been registered. Aside from the accumulation of oxidative lesions, a decrease in antioxidants and succinate dehydrogenase activity, an increase in oxidized glutathione, and enhanced apoptosis via Caspase-3 and BAX overexpression (in the case of terbuthylazine) were observed. Furthermore, terbuthylazine and malathion induced mitochondrial swelling and lactate dehydrogenase leakage in a concentrationdependent manner. Significant upregulation of ubiquitin expression and increasing cathepsin D activity were characteristics that appeared only upon terbuthylazine exposure, whereas induction of IgM was identified as the specific characteristic of malathion toxicity. Pesticides in the studied concentration didn’t provoke significant alterations in the hypothalamic-pituitary-thyroid axis in zebrafish. Co-exposure increased adverse effects of individual pesticides to zebrafish. This study should improve understanding of the mechanisms of pesticide toxicity that leads to fish impairment and biodiversity decline, as well as emphasize the importance of paying attention to pesticide traces in the environment and fish, which can have devastating effects on biota even at low concentrations.
Cheng Ho Mosque and Islamic Education: Chinese Muslim Ethnic Assimilation Strategy in Contemporary Religious Education in Indonesia
Authors: Raya Moch. Khafidz Fuad 
Published: January 2023

Abstract
This article aims to explore how ethnic Chinese Muslims assimilated into Indonesian society from the efforts to build the Cheng Ho Mosque and the establishment of Islamic educational institutions. In the contemporary era, these ethnic minorities can blend in with indigenous Indonesians by engaging in wider Islamic practice activities in the public sphere. The Cheng Ho Mosque and Islamic education are negotiating tools for ethnic Chinese Muslims in establishing a ‘Chinese’ identity in the archipelago’s culture. Focused on three areas: Surabaya City, Banyuwangi Regency, and Pasuruan Regency; this study uses a qualitative as approach and ethnographic as the method. Through Spradley’s analysis, this study finds that the Cheng Ho Mosque is an assimilative strategy of Chinese Muslims in confirming their identity as ‘Indonesian Islam’. Not only as a place of worship for Chinese Muslims, but also as a ‘Islamic Chinese Centre’ and establishing Islamic educational institutions ranging from kindergartens to Islamic boarding schools (pesantren) in a ‘Chinese’ style. This study contributes that the Cheng Ho Mosque and Islamic education have inspired moderate religious practices where minority Muslim communities can exist in Indonesia by assimilation of religious culture and Islamic education.
Nonautonomous Lienard systems equivalent to first-order differential equations
Authors: Adjaï K. K. D. , Akande J. , MONSIA M. D. 
Published: January 2023

Abstract

Generally, second-order differential equations are mapped onto first-order equations to determine their solutions. In the present paper, first-order differential equations with well-known analytic properties are transformed into new or known nonautonomous Lienard differential equations to obtain their exact solutions using the theory of second-order differential equations based on the existence of a first integral recently introduced in the literature by the present authors. First-order differential equations that appear in the Kamke book are used as illustrative examples. As a result, these examples show that parametrically excited Lienard equations may not exhibit parametric resonance.
Liquid extraction of thiophene from n-paraffins (C 8 , C 10 or C 12 ) using two ionic solvents [mebupy][BF 4 ] or [emim][CH 3 SO 4 ]
Authors: Al-Jimaz Adel S. , Alkhaldi Khaled H. A. E. , Aljasmi Abdullah , AlTuwaim Mohammad S. 
Published: January 2023

Abstract
Desulfurization of gasoline and diesel models is investigated through liquid-liquid extraction of thiophene (C4H4S) from n-paraffin compounds. Ionic solvents of 4-methyl-N-butylpyridinium tetrafluoroborate [mebupy][BF4] or 1-ethyl-3-methylimidazolium methylsulfate [emim][CH3SO4] as selective solvents, have been evaluated at 313.15 K and atmospheric pressure of 101.3 kPa. Experimental liquid–liquid equilibrium (LLE) data for the six ternary systems of n-octane, n-decane or n-dodecane + thiophene + [mebupy][BF4] or [emim][CH3SO4], were used to calculate the values of the thiophene distribution ratio, selectivity and efficiency of ionic solvents. The experimental data were correlated using the UNIQUAC equations, and the binary interaction parameters have been reported. The phase diagrams for the ternary mixtures including both the experimental and calculated tie-lines have been presented.
Dissolved nitrogen concentration in river water and its impacts on downstream brackish-estuary lakes in the Bekanbeushi River and Lake Akkeshi catchment, northern Japan
Authors: Nakazumi Naoki , Inoue Takahiro , Nakaoka Masahiro , Fukuzawa Karibu , Shibata Hideaki 
Published: January 2023

Abstract
To clarify the effects of land use in a catchment on river water quality, its nutrient environment and primary production in downstream brackish-estuary lakes, we observed nutrient concentrations (nitrogen and phosphorus) in river and lake water and analyzed land use in the catchment. The concentration of nitrate-nitrogen tended to increase in river water associated with a high percentage of agricultural land (pastureland) in its catchment. It is suggested that nitrogen management in agricultural lands in the catchment area and the arrangement of forests and riparian wetlands and their nitrogen removal functions may have an important effect on the productivity of aquatic organisms and food webs in downstream lakes, especially near river estuaries.
Influence of ionic liquids in the reverse water-gas shift reaction: a thermodynamic study
Authors: Abreu Valdeir A. , Alcantara Murilo L. , Ferreira Newton L. , Bresciani Antônio E. , Bassani Gabriel S. , Nascimento Cláudio A. O. , Alves Rita M. B. 
Published: January 2023

Abstract
Carbon dioxide (CO2) conversion processes can be a promising alternative to replace conventional processes toward a more sustainable industry. The addition of ionic liquids (IL) was reported to increase the performance of related reactions; however, their thermodynamic influence in the reactive chemical equilibrium has been poorly investigated. This study evaluated the effect of the ionic liquids (ILs) [BMIm]BF4], [BMIm][PF6], or [BMIm][NTf2] on the CO2 hydrogenation to carbon monoxide (CO) chemical equilibrium. Predictive and nonpredictive approaches based on the Predictive Soave-Redlich-Kwong equation of state were applied to represent pure ILs densities and vapor pressure. The nonpredictive approach presented the most suitable representation and was applied to represent binary vapor-liquid and liquid-liquid phase equilibria of ILs + CO2, hydrogen (H2), CO, or water (H2O). The influence of temperature pressure, and IL content on CO2 hydrogenation to CO reaction were evaluated. Higher ILs’ molar ratio increased the equilibrium conversion. IL-containing systems are significantly influenced by pressure, and high pressures enhance CO2 conversion. High temperatures increased the reaction’s conversion of systems containing the hydrophobic ILs [BMIm][PF6] or [BMIm][NTf2], while low temperatures increased the CO production of systems containing the hydrophilic IL [BMIm][BF4]. This effect was attributed to the high influence of temperature on the water sorption in the IL. The hydrophilic IL, [BMIm][BF4], promoted the highest increase in CO2 conversion. At 348 K and 2.0 MPa, the CO2 conversion was increased from 1.1–54.1%; roughly an increase of ~ 50 times the original conversion without IL addition.
Knowledge and attitude of school students Regarding the COVID-19 pandemic
Authors: Waghmare Puja , Humane Sushil , Shaikh Tasleem 
Published: January 2023

Abstract
Introduction

In India, a variety of approaches was adopted to control the spread of Covid-19 among people including social distancing, compulsion on wearing a mask, vaccination, etc. however, there is still lacking the awareness among people regarding Covid-19. knowledge and attitude of the youth can make a huge difference in these efforts and so this study is aimed to find the knowledge and attitude of school students regarding Covid-19.

Method

A descriptive study was conducted in September 2021 on a total of 286 school students. Different schools in Nagpur were used to collect data from students aged between 15–18 years. Prior consent and accent were taken from the parent and students respectively before data collection. A convenient sampling technique was used to collect data by using the demographic form, structured knowledge questionnaire(SKQ), and Attitude Likert scale(ALS). Statistical analysis was performed using in Microsoft Excel sheet and a chi-square test was used to calculate the association between the demographic variable and knowledge and attitude score.

Result

In the study group, 37.06% were in 16–17 years of age, 57.69% were male, 32.87% were in 11th standard, about 55.94% of student’s parents were doing the private job, 39.51% of student’s family income was between 10001–20000, 46.85% students were living in a nuclear family, 48.95% students were Buddhist, 89.16 students had previous knowledge of COVID-19 and about 71.37% of student got this knowledge from the television. In the study group, 5.94% of students had Good knowledge and 35.66% of students had a favorable attitude,

Conclusion

The majority of the school students have poor knowledge and attitude toward Covid-19. Educational intervention is very necessary to improve the knowledge of students.
Cut-off values of geriatric nutritional risk index for cardiovascular events in acute myocardial infarction patients
Authors: Ito Satoshi , Inoue Yasunori , Nagoshi Tomohisa , Aizawa Takatoku , Kashiwagi Yusuke , Morimoto Satoshi , Ogawa Kazuo , Minai Kosuke , Ogawa Takayuki , Yoshimura Michihiro 
Published: January 2023

Abstract
Low Geriatric Nutritional Risk Index (GNRI) in patients with heart failure is associated with poor prognosis. However, the usefulness of GNRI for patients with acute myocardial infarction (AMI) remains controversial. We evaluated the optimal cut-off values of GNRI for cardiovascular events in AMI patients by time-dependent receiver operating characteristic (ROC) analysis to examine its usefulness. We retrospectively investigated the optimal cut-off values for two endpoints of all-cause death and major adverse cardiac events (MACE: all-cause death, non-fatal myocardial infarction, hospitalization for heart failure, stroke) over 48 months in 360 patients with AMI who required emergency admission to our hospital between January 2012 and February 2020. The cumulative incidence of MACE over 48 months was 11.6%. The cut-off value of GNRI for all-cause death was 82.7 (AUC 0.834) at 3 months, 89.3 (AUC 0.861) at 12 months, and 90.3 (AUC 0.854) at 48 months. The cut-off value of GNRI for MACE was 83.0 (AUC 0.841) at 3 months, 95.7 (AUC 0.863) at 12 months, and 95.3 (AUC 0.821) at 48 months. Time-dependent ROC analysis showed that the optimal cut-off value of GNRI varied over time. The optimal cut-off value of GNRI is a useful predictor for prognosis in patients with AMI.
Liquid-phase Alkylation of Toluene by Benzyl Alcohol over Micro-mesoporous Hierarchical Mordenite Zeolite
Authors: Bandyopadhyay Rajib , Koshti Hardik 
Published: January 2023

Abstract
In this work, post-synthetic effective acid (HNO3) and base (NaOH) etching technique are used to create hierarchical mordenite having different pore structure. The powder X-ray diffraction (P-XRD) technique was used to confirm the crystalline structure of the base modified and acid modified mordenite. Field emission-Scanning electron microscope (FE-SEM) was employed to confirm the structural morphology of the materials. The modified mordenite were further characterized by Inductive coupled plasma-optical emission spectrometry (ICP-OES), N2 adsorption-desorption isotherms, thermogravimetric analysis (TGA), acid base titration, to confirm the structural integrity, presence of active acidic sites, and other vital parameters. The structure was well conserved after the change, as evidenced by the characterization. The toluene alkylation with benzyl alcohol using hierarchical Mordenite and H-Mordenite produced mono-benzylated toluene. Comparison between acid treated, base treated and H-Mordenite was done. All samples were catalytically active as proved by the catalytic result in the alkylation reaction. The results show that the base alteration dramatically enhances the mesoporous surface area of H-Mordenite. Furthermore, the acid treated Mordenite had the highest benzyl alcohol conversion (75%), but the base modified Mordenite had benzyl alcohol conversion of 73% with the highest mono-benzylated toluene selectivity (61%). The process was further optimised by varying the reaction temperature, duration, and catalyst quantity. Gas Chromatography (GC) was used to evaluate the reaction products and gas chromatography-mass spectrometry (GC-MS) was used to confirm them. Introduction of mesoporosity in the microporous Mordenite was found to have significant effect on their catalytic activity.
CAA-PPI: A Computational Feature Design to Predict Protein-Protein Interaction using different Encoding Strategies
Authors: Mewara Bhawna , Sahni Gunjan , Lalwani Soniya , Kumar Rajesh 
Published: January 2023

Abstract
Protein-protein interactions (PPIs) carry out an extensive variety of biological procedures, containing cell-to-cell interactions, metabolic and developmental control. PPI is becoming one of the most important aims of system biology. PPI act as a fundamental part in predicting the protein function of the target protein and drug ability of molecules. Abundant work has been done to nurture methods to predict PPIs computationally as this supplements laboratory trials and offers cost-effective way of predicting the most likely set of interactions at the entire proteome scale. This article presents an innovative feature representation method (CAA-PPI) to extract features from protein sequence using two different encoding strategies and then an ensemble learning method, the Random Forest method is used as a classifier for PPIs prediction. CAA-PPI considers the role of trigram and bond of given amino acid with its nearby ones. The proposed PPI model achieves more than 98% prediction accuracies with one encoding scheme and more than 95% prediction accuracies with another encoding scheme respectively for the two diverse PPI datasets i.e. H. Pylori and Yeast. Further investigations are made to compare the CAA-PPI approach with existing sequence-based methods and reveals the proficiency of the proposed method with both encoding strategies. To further assess the practical prediction competence, a blind test has implemented on five other species’ datasets independent of the training set, and obtained result ascertains the productivity of CAA-PPI with both encoding schemes.
Improving Eighth Graders’ Vocabulary Mastery through Students’ Learning Style-VARK-Based Flashcards
Authors: Nurhaliza  , Sari Valentina Dyah Arum 
Published: January 2023

Mastering vocabulary will help students in expressing their ideas or understanding others in an EFL context. However, it turns out that students have difficulty learning English due to a lack of vocabulary mastery. Therefore, the selection and the use of appropriate media were needed to help students achieve the learning objectives. In this study, the VARK questionnaire was distributed to students to see their learning styles. The results were that most of them are Read/Write type of learners. Considering that fact, students learning style VARK-based flashcards were implemented as a medium in this Classroom Action Research. This study aims to find out how flashcards can improve vocabulary mastery in class VIII C students of one state Junior High School in Teluk Keramat, Kalimantan. This study applied Classroom Action Research with 2 cycles with 33 student participants. The data analysis technique used mixed-method research; qualitative and quantitative. The instrument used questionnaires, interviews, observation checklists, and tests. The results indicated that students gained improvement after learning by using flashcards media. It was found that the average score of students in the pre-test was 34.9, post-test cycle I was 54.2, and post-test cycle II was 72.5. This proved that students' vocabulary mastery by using students' learning style VARK-based flashcards was improved. Further, it could be concluded that students learning style VARK-based flashcards gave a positive impact on the use of learning media in a Junior High School in Teluk Keramat to improve their vocabulary mastery.
Trends and patterns of cholera epidemic in West Africa: a statistical modeling study
Authors: Conde Amadou , Dureh Nurin , Ueranantasun Attachai 
Published: January 2023

Abstract
Cholera is a serious disease that affects a huge number of people, especially in underdeveloped nations, and is particularly prevalent in Africa and southern Asia. This study aimed to determine cholera incidence trends and patterns in West Africa, as well as to develop a statistical model for cholera incidence. The outcomes of this study were occurrence, which was given a value of 1 if a case occurred and a value of 0 otherwise, and incidence rate. Logistic regression was used to model occurrence, while log-linear regression was used to model incidence after excluding the records with zero cases. The trend of cholera incidence rate was approximately constant for the Democratic Republic of Congo, whereas rates vary substantially throughout the study period in other countries. A confidence intervals plot shows that cholera incidence was higher in September and October, lower in 2015–2017, higher in Guinea, Niger, and Congo (west), and lower in Cote de-Ivoire, Cameroon, the Democratic Congo and Central African republics, Togo and Guinea Bissau. These two models can fit the data quite well. As a result, the method used in this study may be considered as an alternative to the traditional Poisson regression and negative binomial regression models.
Analysis of the effect of using divalent and trivalent iron compounds on sludge dewatering performance in thickening units
Authors: Alamatian Ebrahim , Đurin Bojan , Dadar Sara , Nakić Domagoj 
Published: January 2023

Abstract
Sludge is one of the by-products of wastewater treatment plants (WWTPs). To assist biological processes, part of the produced sludge is returned to the treatment process and the excess is removed from the treatment plant whereby it undergoes thickening and dewatering. Numerous studies have been conducted to investigate the effect of different coagulants on dewatering from sludge, but the effect of using divalent iron for this purpose has not been investigated so far. In this research, the effect of divalent and trivalent iron compounds (ferrous sulfate and ferric chloride) on the dewatering of excess sludge of the first module of the Bojnourd WWTP (Iran) has been investigated. In this regard, first, the effect of different doses of each coagulant to optimize the dewatering characteristics of sludge was investigated and then the effect of pH change by adding lime was investigated. The results showed that the addition of optimal doses of FeSO4 (0.6 and 0.4 g/l) and lime (0.664 and 1.5866 g/l) reduced the capillary suction time of sludge by 30.6 and 32.7%, respectively, while reducing the moisture content of sludge cake by 26 and 30.6%.
Hydraulic characteristics of flow over stepped and chute spillways (case study: Zirdan Dam)
Authors: Salmasi Farzin , Abraham John 
Published: January 2023

AbstractStepped spillways are suitable and economical options for high-storage dams that require significant energy dissipation, structural adaptation to roller-compacted concrete dams, and spontaneous flow aeration. In this study, a numerical analysis of the hydraulic characteristics for the skimming flow regime of the stepped spillway of Zirdan Dam is carried out. A comparison between the flow characteristics for stepped and smooth spillways is provided. By preparing numerical models of the spillway using the k-ε RNG turbulence model and the multiphase mixture method, a hydraulic analysis of the flow was completed. To verify the performance of the numerical model, field data were collected and used for validation. The results show that the presence of steps along the spillway cause a significant reduction in the length of the boundary layer and faster aeration occurs. In a stepped spillway, the cavitation index is higher than the critical limit along the entire length of the spillway. Thus, the risk of cavitation and destruction is negligible. On the other hand, with a smooth spillway, the possibility of cavitation may occur. This negative effect (negative pressures) occurs 56 m from the crest of the spillway on the downstream side.
Dam inflow prediction using large-scale climate variability and deep learning approach: a case study in South Korea
Authors: Han Heechan , Kim Donghyun , Wang Wonjoon , Kim Hung Soo 
Published: January 2023

AbstractAccurate prediction of dam inflows is essential for effective water resources management in terms of both water quantity and quality. This study aims to develop a Long Short-Term Memory (LSTM) deep learning-based monthly dam inflow prediction model using large-scale climate indices. Six climate indices, Atlantic multidecadal oscillation (AMO), El Niño–southern oscillations (ENSO), North Atlantic oscillation (NAO), Pacific decadal oscillation (PDO), Niño 3.4, and Southern Oscillation Index (SOI) for the period of 1981–2020, were used as input variables of the model. The proposed model was trained with 29 years of data (1981–2009) and tested with 12 years of data (2009–2020). We investigated 29 input data combinations to evaluate the predictive performance according to different input datasets. The model showed the average values of metrics ranged from 0.5 to 0.6 for CC and from 40 to 80 cm for root mean square error (RMSE) at three dams. The prediction results from the model showed lower performance as the lead time increased. Also, each dam showed different prediction results for different seasons. For example, Soyangriver/Daecheong dams have better accuracy in prediction for the wet season than the dry season, whereas the Andong dam has a high prediction ability during the dry season. These investigations can be used for better efficient dam management using a data-driven approach.