bluuebunny/crossref_metadata_2025 huggingface dataset:
Post-COVID-19 Pandemic Effect on University Students’ Fitness Level
Authors: Ciomag Rela Valentina , Pop Cristiana Lucretia , Nae Ionela Cristina , Filip Cristina
Published: August 2024

Background and Study Purpose: Through the present paper, we aimed to determine to what extent physical capacity was affected by the restrictions during the pandemic. This confirmatory study hypothesises that university students’ fitness level and effort capacity decreased after the pandemic compared to the results obtained before sanitary restrictions. Material and Methods: Fifty female students at the economic faculties, part of two groups of 25 each, in the age range between 19 and 21, passed six physical tests. The applied physical tests targeted strength (sit-ups and squads in 30 s), power (standing long jump), flexibility (sit and reach), coordination (Matorin test), and cardio-respiratory fitness level (Ruffier test). Results: All test results, except one, demonstrate a statistically significant difference, confirming the hypothesis that the two samples differ in strength, power, flexibility, coordination, and cardio-respiratory fitness. By calculating Cohen d effect size, the standardized mean difference of the pandemic effect demonstrates how substantially different are the two samples. Conclusions: This study compares objective results of standardised fitness tests in two successive samples of young women that can contribute to a better understanding of the long-term impact of the pandemic breakdown on the fitness level. The physical abilities decrease between 10 and 28 per cent, with the most worrying level recorded at flexibility and abdominal strength tests. Remedial measures are needed to reverse the physical potential decrease of young adults after the sanitary crisis. A diminished physical potential of the future educated workforce would have lasting effects on their physical and mental health with higher healthcare expenditure and economic consequences due to a resilience and productivity decrease.
Professional Education of Adults: Technological Challenges in the Context of Neuroscience
Authors: Tymchuk Liudmyla , Vieilandie Liliia , Pavlova Valeriia , Prokofyeva Lyubov , Tadeush Olena , Bogdan Zhanna
Published: August 2024

The article explores neuroscientific processes underpinning today’s societal development, characterized by globalism, integration and informatization as technological challenges in adult professional education. Human development is viewed as an ongoing learning process, during which individuals constantly seek new experiences while transcending physical and conceptual boundaries across various industries, fields and styles. This extensive globalization serves as a dominant worldview and a guiding artistic direction. One lives in a new era marked by significant social advancements, scientific breakthroughs and extraordinary technological capabilities, particularly driven by the high-speed Internet, which play a crucial role in the evolution of neuroscience and highlights the importance of this research. In a world that is globalized and technologically advanced, ongoing learning and development are crucial to tackle integration processes and difficulties. Lifelong learning and self-enhancement are particularly vital for adults, especially in an increasingly competitive environment where individuals are expected to refine their knowledge and skills to deal with new social challenges effectively. This article aims to identify the neuroscientific factors that influence the evolution of adult professional education. It employs such methods as synthesis and analysis of adult extracurricular education in the context of neuroscientific insights. The findings indicate that competence in any field is cultivated throughout one’s lifetime.
Pregnant and Postnatal Women’s Views on Resources for Quitting Smoking: “Every Person Is Different So These Things Depend”
Authors: Small Sandra P. , Brennan-Hunter Andrea , Yi Yanqing
Published: August 2024

OBJECTIVE:Maternal smoking during pregnancy or postnatally contributes to significant harm, including stillbirth, preterm birth, low birth weight, and sudden infant death. Alternatively, maternal smoking cessation benefits the health of the woman and child. Informational resources may be helpful for maternal smoking cessation. The objective of this study is to examine such resources from the perspectives of pregnant and postnatal women who smoked.

METHODS:The study was a cross-sectional survey design with quantitative and qualitative data. There were 164 participants: 120 pregnant and 44 postnatal.

RESULTS:About 29%–59% of women accessed various resources for smoking-related information. Of those, some perceived the resources as helpful, while others did not share that view. Mixed perceptions of the helpfulness of resources were also the case for women’s preferences for resources for quitting smoking. Women offered suggestions for specific information and support they thought would be helpful for quitting smoking during pregnancy or postnatally. Helpful information consisted of (a) realistic messages about the harmfulness of smoking to the fetus, child, and woman and realistic messages involving shared personal experiences of smoking and quitting smoking during pregnancy and (b) advice about how to quit smoking during pregnancy or postnatally. Helpful support consisted of (a) nonjudgmental understanding, (b) assistance to deal with stress and personal issues, and (c) tangible aid for smoking cessation.

CONCLUSION:The findings suggest that a variety of informational and support resources are necessary and should be readily available to meet the individualized needs of pregnant women or postnatal women who smoke.
The Relationship Between Self-Control Factors and Household Saving Behavior
Authors: Yoon Dong Won , Hanna Sherman D.
Published: August 2024

We examined the effect of self-control factors on saving behavior based on the behavioral life cycle hypothesis, using the 2016 and 2019 Survey of Consumer Finances datasets. A model that included self-control factors (behavioral life cycle variables) had a more significant effect on saving behavior than a model that included only normative life cycle variables. Among self-control factors, having at least one saving rule was positively associated with saving behavior, but saving goals were not significantly associated with saving behavior. Having a foreseeable major expense was negatively associated with saving behavior. The findings of this study can assist financial planners, counselors, and educators in developing and implementing strategies related to self-control factors to enhance saving behavior.
“She Punched, Punched, and Scratched Me While I Was Holding My Children After We Broke Up”: Men’s Experience of Postseparation Domestic Abuse
Authors: Bates Elizabeth A. , Taylor Julie C. , Hope Katie A. , Smith Jade L.
Published: August 2024

There is a paucity of literature relating to male victims of intimate partner violence and their experiences postseparation. This study explored men’s experiences of abuse after the end of a relationship using an anonymous online survey distributed via social media. The survey included questions of a demographic nature followed by a series of open-ended questions. A hundred and thirty men aged between 18 and 68 years participated. All participants were reporting on their experiences within opposite sex relationships. A thematic analysis identified four master themes (preseparation abuse, postseparation abuse, abuse impact, and help-seeking). The analysis revealed significant experiences of abuse occurring preseparation, followed by accounts of postseparation abuse and the challenges men faced in terms of help-seeking. The collection of preseparation data helped to situate the postseparation experiences in the wider context of an existing abusive relationship and illustrated the impact of this across a range of experiential domains. We conclude that men’s experiences of physical abuse as well as coercive and controlling behavior that exist preseparation often continue postseparation, albeit changing and escalating through different mechanisms. Suggestions for future research and recommendations for practice have been identified.
Dementia- A Review of the Research and Therapeutic Measures
Authors: Kushner Jack
Published: August 2024

As our population ages, we are seeing more and more patients with variations of cerebral dementia. This review cites the symptoms, the neuropathology, the various research trials and ideas, the diagnostic exams, and the treatments commonly used.
Quartz-kyanite-muscovite magmatic mica in Borisovian dikes in the Southern Urals
Authors: Popov V. , Kolisnichenko S. , Blinov I.
Published: August 2024

The article describes the simulation of ontogenesis of rock mineral aggregate with debatable genesis. Lenses or stokes of weakly deformed rocks are found in the South Urals in the block of kyanite-bearing stratified rocks of the Borisovskiye Sopki, the structure of which corresponds to the structures of igneous rocks. Induced surfaces of joint simultaneous growth are observed in all minerals — muscovite, kyanite, quartz, rutile, pyrite, monazite, xenotime and zircon. This is a paragenesis (eutectics). An interesting fact is that large quartz individuals are saturated with muscovite inclusions, while kyanite, synchronous with them, is free from muscovite inclusions, which is explained by repulsion in the melt-solution of minerals with equally charged surface. The mineral aggregate of the studied rocks lacks morphological signs of metasomatism (metacrystals, pseudomorphs, shadows of previous solid bodies) and recrystallization. This indicates magmatic genesis of the studied quartz-kyanite-muscovite rocks.
Non-surgical (liquid) rhinoplasty
Authors: Erwin Dylan Z. , Stallworth Christian L.
Published: August 2024

Non-surgical (liquid) rhinoplasty (LR) is a common and expanding cosmetic procedure. The use and safety of in-office injectables, as well as surgeon comfort, has led to substantial growth with the procedure. Knowledge of nasal structural and vascular anatomy, injectable filler properties and in situ behavior, and procedural technique are all required for the application of non-surgical rhinoplasty. There is consensus regarding common indications for the procedure, including dorsal augmentation, correction of post-surgical deformities, and improvement of nasal tip symmetry. However, there is substantial variability in filler usage, technique, and patient selection. As with surgical rhinoplasty, the risk of patient dissatisfaction with LR remains high. It is of utmost importance to consider the rise of non-surgeon providers performing these procedures. A thorough understanding of the risks, benefits, and proper patient selection are key for any facial plastic surgeon utilizing LR.
Interactive decision support system for lung cancer segmentation
Authors: Sydorskyi Volodymyr
Published: August 2024

This paper studies Clinical Intelligent Decision Support Systems (CIDSSs) for lung cancer segmentation, which are based on deep neural nets. A new interactive CIDSS is proposed and compared with previous approaches. Additionally, the purpose uncertainty problem in building interactive systems is discussed, and criteria for measuring both quality and amount of user feedback are proposed. In order to automate system evaluation, a new algorithm was used to simulate expert feedback. The proposed interactive CIDSS outperforms previous approaches (both interactive and noninteractive) on the task of lung lesion segmentation. This approach looks promising both in terms of quality and expert user experience. At the same time, this paper discusses a bunch of possible modifications that can be done to improve both evaluation criteria and proposed CIDSS in future works.
2-Cinnamamido-4-Methylpentanamide and N-(2-Hydroxypropanoyl)Cinnamamide: Synthesis, Characterization, and Molecular Docking Studies Through PBP2a Protein
Authors: Rasyid Herlina , Ernawati Teni , Monoarfa Indah Muthmainnah
Published: August 2024

ABSTRACT. Cinnamic acid has been found in several types of plants and has a diverse spectrum of bioactivity. Derivatization of cinnamic acid related to the improving bioactivity of a compound. Cinnamic acid can be found as an acid or in conjugated form with amides, esters, aldehydes. This research focus on the synthesis of amide derivatives of cinnamic acid to improve the bioactivity. Two compounds namely 2-cinnamamido-4-methylpentanamide (1a) and N-(2-hydroxypropanoyl)cinnamamide (1b) were carried out through amidation reaction using carbodiimide coupling reagent for 24 hours. The synthesized target compounds were characterized using FT-IR, GCMS-MS, 1H-NMR and 13C-NMR spectroscopy. The compounds were evaluated their antibacterial activity by molecular docking simulation against PBP2a (PDB ID: 1MWT) using AutoDock4 and AutoDockTools software. PBP2a is one of the main proteins in MRSA that has evolved to resist β-lactam antibiotics and was proposed to be the most likely target of MRSA. The inhibitory process of this protein works through inhibition of the bacterial cell wall. The synthesis process of 1a and 1b produced yields of 22.13% and 25.20%. Molecular docking results showed that 1a and 1b had better energy (ΔGbinding -7.33 and -6.29 kcal/mol) than Streptomycin as the control positive. The compounds of 1a and 1b had interactions on PBP2a through hydrogen bond with Asn464, Thr600, and Tyr519. This present study showed that the synthesized compounds from cinnamic acid derivatives have a potential to be used as antibacterial agents.
 
Keywords: Amidation, antibacterial, 2-cinnamamido-4-methylpentanamide, molecular docking, N-(2-hydroxypropanoyl) cinnamamide.
The Role of The Ni/HZSM-5 Ratio on The Anisole Hydrodeoxygenation Reaction
Authors: Nugrahaningtyas Khoirina Dwi , Nurcahyo I F , Hidayat Yuniawan , Rahmawati Fitria , Fadlulloh Zaki , Heraldy Eddy , Qurrotul'aini Nisriina 'Abidah
Published: August 2024

ABSTRACT. Bio-oil is a renewable energy source with high oxygen levels, and anisole is a chemical widely employed in research to represent it. Catalytic hydrodeoxygenation (HDO) reduces the oxygen content.  A catalyst known as nickel-modified HZSM-5 has shown promising results for HDO. Meanwhile, catalyst efficiency depends on the Ni/HZSM-5 ratio. So, this study aims to determine how the Ni/HZSM-5 ratio influences the catalyst's properties, activity, and selectivity in anisole HDO. The Ni/HZSM-5 catalyst was made using the wet impregnation method with various ratios of Ni/HZSM-5. The catalysts were analyzed for their morphology using scanning electron microscopy-energy-dispersive X-ray (SEM-EDX). The diffraction patterns were studied using X-ray diffraction (XRD). Surface area and porosity were determined through gas sorption analysis (GSA). Then, the acidity strength was evaluated via temperature-programmed ammonia desorption (NH3-TPD). The characterization results show Ni was successfully impregnated and distributed evenly in HZSM-5 without changing the primary structure. Adding Ni metal to HZSM-5 increases the surface area of the catalyst but reduces its acid strength. The catalytic performance of the catalysts was then evaluated in a flow reactor at 400 °C, using 15 mL/min H2 gas. The liquid products of the reaction were analyzed using gas chromatography-mass spectroscopy (GC-MS). The results of the catalytic performance show that Ni4.5/HZSM-5 has the highest catalytic activity in anisole conversion. At the same time, Ni6.4/HZSM-5 shows the highest selectivity towards benzene-toluene-xylene (BTX).
 
Keywords: Hydrodeoxygenation, nickel, anisole, heterogeneous catalyst, acidity.
In situ Measurement of Phosphate using Fe3O4/Chelex®100-Agarose-Oxalic Acid Hydrogel in Diffusive Gradient in Thin Films
Authors: Dinira Layta , Rumhayati Barlah , Mardiana Diah , Andayani Ulfa
Published: August 2024

ABSTRACT. This study would be the first to develop a novel combination of Chelex®100 and Fe3O4 as a mixed binding gel for in situ phosphate measurement employing Diffusive Gradient in Thin Films (DGT). Fe3O4 and Chelex®100 were utilized as binding agents within a single binding layer for phosphate measurements in laboratory and natural water settings. The synthesized Fe3O4 was identified as magnetite and consisted of micro-sized particles. The pore size of the mixed binding gel ranged from 22.39 to 112.5 µm. Incorporating Chelex®100 with Fe3O4 in oxalic acid cross-linked agarose did not diminish phosphate adsorption efficiency. As adsorption time and phosphate concentration in solution increased, the quantity of adsorbed phosphate in the mixed binding gel also increased. Optimal phosphate elution was achieved using a basic solution, with a phosphate elution efficiency of 95.3 ± 0.4% observed with 0.4 M NaOH. The diffusion coefficient measured using the mixed binding gel was 1.08 times greater than that of polyacrylamide cross-linked with an agarose derivative (APA) gel, typically employed in the DGT technique. Phosphate concentration measurement with Fe3O4/Chelex®100-agarose oxalic acid in a DGT passive sampler at pH 4-8 yielded values twice those in bulk solution. Similar results were obtained when measuring phosphate in a 0.01 – 0.1 M NaNO3 solution. A T-test showed that the phosphate concentration obtained from mixed binding layer-DGT as an alternate passive sampler was not significantly different from grab sampling. This study underscores the suitability of Fe3O4-Chelex®100 impregnated in agarose-oxalic acid gel for monitoring phosphate in natural water via DGT.
 
Keywords: Agarose, diffusive gradient in thin films, mixed binding gel Fe3O4, oxalic acid.
Triterpenoids From Swietenia mahagoni L Jacq. and Their Cytotoxic Activity against MCF-7 Breast Cancer and CV-1 Normal Kidney Cell Lines
Authors: Supratman Unang , Abdullah Fajar Fauzi , Farabi Kindi , Nurlelasari Nurlelasari , Awang Khalijah , Nafiah Mohamad Azlan
Published: August 2024

ABSTRACT. Triterpenoid is a group of natural products with various remarkable activities, including cytotoxic. One of the sources for this type of compounds is Swietenia genus belong to Meliaceae family. This genus known to contains various secondary metabolites including limonoids, flavonoids, and triterpenoids. Especially for triterpenoid, there is limited report on isolation as well as biological activity from Swietenia genus, such as Swietenia mahagoni. In this research, three triterpenoid compounds have been successively isolated and identified from n-hexane extract, namely, (-)-leucophyllone (1), toonaciliatavarin E (2), and moronic acid (3). All isolated were assed against MCF-7 breast cancer and CV-1 normal kidney cell lines. The result showed that only moronic acid (3) performed moderate activity against two cells with IC50 of 63.10 and 48.04 µM, respectively. The other isolated compounds (1 and 2) showed weak cytotoxicity with IC50 > 500 µM. Based on preliminary structure activity relationship, revealed that pentacyclic triterpenoid (moronic acid, 3) showed stronger cytotoxicity compare with tetracyclic triterpenoids (-)-leucophyllone (1) and toonaciliatavarin E (2).
 
Keyword: Cytotoxicity, MCF-7 and CV-1, Switennia mahagoni, Triterpenoids.
Politically connected audit committees and ESG reporting
Authors: Kusharyanti  , Astuti Sri , Marita
Published: August 2024

This study investigates the impact of audit committees with political connections on environmental, social, and governance (ESG) reporting. Drawing from reputational cost theory, it hypothesizes that personal political affiliations of audit committee members positively influence ESG reporting quality. Analyzing data from companies listed on the Indonesia Stock Exchange between 2018 and 2022, the findings reveal that companies with politically connected audit committees exhibit higher levels of ESG reporting compared to their counterparts without such connections. The study highlights that audit committees with political ties are subject to increased litigation risks and reputational costs.
Moderation of tax attitudes on the relationship of knowledge and tax incentives on sustainable MSMEs performance
Authors: Sari Diana , Johan Ahmad
Published: August 2024

Recently, public opinion regarding tax avoidance has become unbreakable; and issues related to tax institutions are disrupting tax revenues. Tax avoidance leads to an issue that still requires resolution and is firmly entrenched among the business community in developed countries. The small and medium business sector refers to a sector that is involved in aggressive tax avoidance practices. Thus, tax can be accepted as a problem to achieve sustainability. This research applies a fiscal psychology theory approach with a survey approach on 150 MSME owners in Bandung City, West Java. The collected data was then analyzed using the Partial least squares approach to test and analyze the hypothesis. The results of this research show that tax knowledge and the tax incentives provided have a positive effect on the sustainable business performance of MSMEs in Bandung. Apart from that, this research also proves that tax attitudes are a determinant that can strengthen or weaken the relationship between tax knowledge and the tax incentives provided in achieving sustainable MSME business performance. It is hoped that the results of this research will add to the literature and expand the body of knowledge, especially in the context of taxation and business performance, and for practitioners, especially business owners. It can be a consideration that compliance in paying taxes is an essential factor in achieving business performance.
Recommender System for Group of Users using Matrix Factorization for Tourism Domain (Case Study: Bali)
Authors: Prabowo Ruh Devita Widhiana , Baizal Z. K. A.
Published: August 2024

Choosing a product that suits a customer's needs requires a recommendation system to provide suggestions on a collection of items of interest to the user. Recommendations can be applied in various fields such as entertainment, shopping sites, social networking, job portals, discovery of relevant web pages, and so on. There are many circumstances where recommendations are needed for a group such as in tourism and entertainment purposes. The development of a Group Recommendation System (GRS) was carried out in response to the need to provide several recommendations to a group of users. We conducted this research to build a GRS that can provide item recommendations using the Collaborative Filtering (CF) method with Matrix Factorization Technique, as well as three approaches, namely After Factorization (AF), Before Factorization (BF), and Weighted Before Factorization (WBF). Determine the best approach for the three categories of groups formed, namely small groups (three members), medium groups (five members), and large groups (ten members). The focus of this research is the tourism destination domain in Bali. In the evaluation results of the precision calculation, the medium group obtained the highest score for the AF, BF, and WBF approaches of 0.944. Meanwhile, in calculating recall, the small group achieved the highest scores for the AF, BF, and WBF approaches of 0.294, 0.259, and 0.259, respectively. From the results of this study, it appears that small groups are suitable for using the BF approach, while the AF method is more effective for large groups, and the best approach for medium groups is the WBF.
Prediction Of Student Achievement Using Artificial Neural Network And Support Vector Regression At SMK TELKOM Lampung
Authors: Susanti Desi , Triloka Joko
Published: August 2024

The analysis of student performance is crucial in vocational schools because it helps identify the challenges students face in preparing themselves for the workforce. By integrating data mining techniques such as Artificial Neural Networks (ANN), educators can enhance their understanding of factors that improve student learning outcomes. An artificial neural network (ANN) is composed of interconnected artificial neurons that can learn from input data and make complex predictions, including academic achievements. The structure and function of the human brain inspire ANN. This study compares the effec- tiveness of the artificial neural network (ANN) method with other methodologies, such as support vector regression (SVR), to predict student achievement at SMK Telkom Lampung. Primary data collected from SMK Telkom Lampung includes 4939 examples with 550 cases, 26 features, and 4 meta-attributes. Performance evaluation involves metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and coefficient of determination (R2). The coefficient of determination (R2) value of the Neural Network at 0.001 is higher than the R2 value of SVR, which reaches -0.036. Research find- ings indicate that the Artificial Neural Network model slightly outperforms the Support Vector Regression model, with lower prediction error rates and better ability to explain data variability.
Equal Incremental Cost Method with Adjustable Gamma Control to Solve Generator Scheduling
Authors: Rahmat Basuki , Wijaya I Gede Putu Oka Indra , Ikhsan Rifki Rahman Nur , Yustika Lindiasari Martha , Raharjo Jangkung
Published: August 2024

Generator scheduling remains an intriguing issue within the energy industry. It relates to the optimization of production costs, where system operators must select the optimal combination of available resources to minimize production costs. This paper proposes an enhancement to the Equal Incremental Cost (EIC) Method using Adjustable Gamma Control (AGC) in generator scheduling. Iterations begin with an initial lambda value, then gradually increase with the application of the  factor until power demand is met. A  variable of 10% is used as an adjustment step in the optimization method. The proposed method is capable of achieving convergence with 100% accuracy, where the power generated by all generators precisely matches the load demand (2,650 MW), at a cost of USD 32,289.03. EIC-AGC ranks second-best after VLIM, albeit with the consequence of consuming 195 seconds. This method is expected to have a significant impact on designing highly accurate economic dispatch techniques. Thus, generator scheduling will lead to a reduction in operational costs compared to current practices.
Development of Smart Hydroponics System using AI-based Sensing
Authors: Putra Septafiansyah Dwi , Heriansyah Heriansyah , Cahyadi Eko Fajar , Anggriani Kurnia , Imron S Jaya Moh Haris
Published: August 2024

This paper proposes a smart hydroponic system that operates automatically using a fuzzy logic algorithm, integrating IoT functionalities to support smart agriculture. The system allows for remote monitoring and control via the internet, providing real-time data on water levels, pH levels, temperature, and nutrient solution temperature. Precise dosing and temperature control are critical for optimal plant growth, and the system schedules temperature measurements to ensure stability. Unstable temperature can affect pH levels, thereby impacting nutrient absorption. The proposed system employs sensors to continuously monitor the electrical conductivity (EC) and pH levels of the nutrient solution. Fuzzy control is utilized to regulate the nutrient solution pump, automatically adjusting EC and pH levels to promote optimal plant growth. This approach reduces the time burden on producers and provides more precise control over the nutrient solution, resulting in improved growth outcomes. The main contributions of this work are as follows: the development and implementation of an AI-based system integrating a controller, IoT environment, fuzzy logic algorithm, and NFT (nutrient film technology) hydroponics; the creation of a user-friendly interface for farmers through the Smart-Hydroponic application, enabling hybrid monitoring and control of hydroponic farms;  the establishment of an IoT-based cloud environment for sensor data monitoring; the implementation of a smart hydroponic system for nutrient sensing, monitoring, and control; and  a comparative analysis between smart and conventional hydroponics based on morphological results.
On the estimation of integral risk of predictor Lipschitz functions in machine learning models
Authors: Chaynikov Yuri Sergeevich , Sudakov Vladimir Anatolievich
Published: August 2024

Class imbalance in available training samples for solving machine learning problems in most practical cases complicates the training of predictors that effectively generalize patterns from the training dataset to the general population. This paper investigates the theoretical foundations of the effectiveness of adding synthetic data to the training set. In the assessment of overall risk, two types of errors are highlighted: representation error and deviation error. Practical recommendations are formulated for creating synthetic samples that deviate in their distribution from the representative ones by the density distribution of the argument, with more frequent samples in those areas where the density distribution of the argument has relatively low values, leading to a reduction in the size of the corresponding Voronoi cells and a reduction in the contribution of deviation error to total risk.
BETWEEN TWO CRISES: DO ISLAMIC BANKS SUFFER?
Authors: Grassa Rihab , Sarea Adel , El-Halaby Sherif , Damak Anissa Naouar
Published: August 2024

This study compares the effects of the Global Financial crisis and COVID-19 pandemic on the Islamic banking sector in the Gulf Cooperation Council (GCC). Using a sample of 32 Islamic banks observed over the period 2006 to 2020, the paper reveals that the two events have different effects on the Islamic banking sector. Overall, Islamic banks are not as profitable and resilient in the COVID-19 pandemic as in the global financial crisis. However, Islamic banks in GCC countries has gained experience and become more efficient and stable over time. The policy implication of this study supports digitalization and the increased prominence of financial technology (Fintech). In addition, monetary authorities in the GCC have to introduce innovative products to help the Islamic banking sector to be more resilient to such crises.
Bridgmanite megacrysts drive segregation of the terrestrial magma ocean
Authors: DENG JIE , Hu Junwei , Shi Yidi , Lee Jina , Niu Haiyang , Stixrude Lars
Published: August 2024

The solidification of the deep and global magma ocean 4.5 billion years ago likely stands as the most significant differentiation event in the Earth’s history, setting the initial conditions for its subsequent evolution1. However, our understanding of this solidification process remains limited, partly due to a lack of knowledge regarding the grain size of Earth’s most abundant solid phase, bridgmanite2-5. In this study, we employ a combination of cutting-edge techniques, including machine learning potentials, seeding, and enhanced sampling, to investigate the crystallization of bridgmanite using large-scale molecular dynamics simulations consisting of up to 1 million atoms. Our primary focus is on elucidating the key parameters controlling nucleation and grain growth processes, in particular the least-constrained crystal-liquid interfacial energy. Our results demonstrate a significant pressure-dependent increase in interfacial energies of bridgmanite-liquid, surpassing those of silicate-liquid systems at ambient pressure by a factor of up to ten6-8. Within a convective magma ocean, this amplified interfacial energy allows bridgmanite crystals to reach at least decimeter-scale regardless of the nucleation mechanism, driving efficient fractional crystallization and causing substantial chemical differentiation and mantle compaction. The large crystal sizes imply the existence of highly viscous convective cores of the lowermost mantle, promoting the preservation of primordial signatures in Earth's deep interior. Our study sheds light on the enigmatic solidification of Earth’s magma ocean, offering crucial insights into the early evolution and compositional heterogeneity of our planet.
WITHDRAWN: Green Synthesis of Silver Nanoparticles and Effects on Winter Wheat and Barley Varieties
Authors: Minic Djordje D , Mladenovic-Markovic Katarina , Kesic Ana , Grujovic Mirjana , Markovic Stefan , Torbica Aleksandra , Djukic Nevena
Published: August 2024

Cereals are exposed to various external conditions during the growing period, which affects their growth, development, and yield. Silver nanoparticles represent a potential solution for alleviating the negative effects of temperature stress. This study examines the impact of silver nanoparticles on extract yield, proline concentration, and antioxidant activity of winter wheat and barley during the tillering phase under winter field conditions. Silver nanoparticles (AgNPs) were synthesized using a green method with an aqueous extract of Agrimonia eupatoria L. Two varieties of winter cereals, Simonida (Triticum aestivum L.) and Nonius (Hordeum vulgare L.), were foliarly treated with concentrations of 5 mg/ml and 10 mg/ml AgNPs-H2O. The experiment lasted for 10 days, during which the minimum temperature recorded was -7°C in field conditions. Proline concentration was higher in both varieties treated with nanoparticles compared to the controls. Antioxidant activity was assessed using the DPPH method on untreated and treated AgNPs-H2O samples, with evaluation of the antioxidant activity of the nanoparticles themselves and ascorbic acid as a positive control. Results showed that AgNPs-H2O increased proline concentration and antioxidant activity in both tested winter cereal varieties compared to the controls, while extract yield was higher with the application of certain concentrations. This highlights the potential of AgNPs-H2O to improve the tolerance of winter cereals to cold and low temperatures through increased antioxidant activity.
High performance velocity analysis for multi-AVO seismic data
Authors: XU Yankai , Li Jiawei , Qi Jiao , Cao Siyuan , Liu Hongwei , Li Weiling , Zhu Hongduo
Published: August 2024

Improving the velocity spectrum resolution is challenging because the field data contains some noise and polarity inversion in many cases. Although the AB semblance and local similarity method can deal with the seismic data with single polarity reversal, they do not perform as well for noisy and multi-AVO data. In this paper, we proposed a symbolic-weighted velocity analysis velocity spectrum analysis method to solve these problems. Firstly, to correct the polarity of multiple AVO seismic data, we adopt a technology using the symbolic information between adjacent traces. Then, considering the singular value distribution characteristics of seismic data in velocity scanning, the RSVD algorithm which is a modified mode of the singular value decomposition is used to improve the recognition sensitivity of hyperbolic events and suppress the influence of noise. Synthetic and field examples demonstrate that, compared with conventional semblance, local semblance and SBWS, the proposed method has higher precision and stronger anti-noise performance for the noisy multi-AVO seismic data.
The effects of 12 weeks of high-intensity interval rope skipping training on speed qualities in male soccer players: a randomized controlled trial
Authors: Wei Bo , Qiu Jiangang
Published: August 2024

Objectives: This study was to investigate the effects of high-intensity interval jump rope training on the speed qualities of soccer players.
Design: Randomized controlled trial
Methods: T Methods: Twenty-five elite soccer players were randomly assigned to an experimental group (N=13) performing high-intensity interval jump rope training and a control group (N=12) undergoing traditional training for 12 weeks. Both groups trained two times per week. Speed qualities were assessed using 30-meter sprint, Optojump rapid frequency and visual reaction tests, T-run test, and standing long jump. Data were analyzed using Two-factor repeated measures ANOVA.）
Results: High-intensity interval rope skipping training could improve sprint speed (P=0.000***), movement speed (P=0.000**), visual reaction speed (P= 0.000**), change of direction speed (P= 0.000**), and explosive speed (P= 0.000**). Further, compared to traditional training methods, high-intensity interval rope skipping training was more effective in sprint speed(P=0.033**) and visual reaction speed(P= 0.010**).
Conclusions: High-intensity interval rope skipping training can improve the speed quality of soccer players, especially in sprint speed and visual reaction speed.
Tea extracellular vesicles attenuates NAFLD via reducing TG levels by inhibited MTTP gene methylation
Authors: Liu Liang , Wang Huan , Zou Yigui , Xu Xichao , Zeng Yinzhen , Li Wenwen , Bai Daming , Dai Dongling
Published: August 2024

Background: Therapeutic effect of traditional medicines for nonalcoholic fatty liver disease (NAFLD) is far from satisfactory. Tea has been shown to have efficacy in preventing NAFLD. We hypothesized that tea derived extracellular vesicles (TDEVs) may attenuate NAFLD.
Methods: Extracellular vesicles (EVs) were isolated from fresh tea. High Performance Liquid Chromatography (HPLC) was used to detect the epigallocatechin-3-gallate (EGCG)in TDEVs. Oleic acid-induced HepG2 cells were treated with different doses of TDEVs. Oil red O staining and fluorescent staining were used to analyze TDEVs efficacy in NAFLD HepG2 cell model. Enzyme‑linked immunosorbent assay (ELISA) was applied to evaluate the levels of triglycerides (TG) and interleukin 6 (IL-6). Q-PCR technique was used to detect the mRNA expressions of MTTP, and Western Blotting was applied to evaluate their protein expressions. Bisulfite genomic sequencing was used to analyze the level of DNA methylation within the promoter of MTTP gene.
Results: The concentrations of EGCG in TDEVs was 1.031 ± 0.044 mg/ml, equivalent to 5.6 mg/100 g/FW. Oil red O staining and fluorescent staining demonstrated TDEVs absorbed by HepG2 cells contributed to oil droplets decomposition and a consequential decrease in TG and IL-6 levels. Q-PCR and Western Blotting showed an upregulation in MTTP gene expression by TDEVs. Bisulfite genomic sequencing analysis revealed a reduction in the methylation level of MTTP gene in TDEVs groups.
Conclusion: The results of this study indicated that TDEVs attenuated NAFLD via reducing TG level by inhibition of MTTP gene methylation in NAFLD cell model.
Evaluation of hydro-physical properties along a northern boreal bog peatland transect
Authors: Whittington Pete , Koiter Alex
Published: August 2024

Advances in peatland ecohydrological modelling highlight the need for higher resolution depth profiles of important soil physical properties. Peatland soil profiles exist as a continuum from Sphagnum-dominated surface cover to highly decomposed peat at depth. We determined the bulk and particle density, porosity, saturated hydraulic conductivity (Ksat), and von Post in a northern bog to a depth of ~ 200 cm in 5-cm intervals along a transect extending from a moderately treed to a more open area. The bulk and particle densities and von Post scores increased, and porosity decreased with depth. The particle density had a relatively abrupt shift near ~ 75 cm changing from ~ 0.8 g cm− 3 to a relatively consistent ~ 1.4 g cm− 3. The variability measured was small in the upper ~ 25 cm, larger at depths of ~ 25–125 cm, and became more moderate at depths > ~ 125 cm (but not particle density). The variability of bulk density at the deeper depths results in the observed variability of porosity as well. The larger variability in physical properties roughly coincides with the abrupt shift in the magnitude of measured properties suggesting that contemporary processes and/or past events (e.g., wildfire) could be responsible for this pattern. Bulk and particle density and porosity exhibited a relationship with the von Post score with an abrupt shift in values between von Post scores of 3 and 4. Detailed examination of peatland soil properties will improve the robustness and reliability of models and may reveal additional information on the history and processes of formation.
More than the sum of their parts: Behavioral Tractography analysis of distress wellbeing and context reveal dynamic signatures of psychosis and autism
Authors: Sandini Corrado , Imparato Andrea , Feller Clemence , Ilen Laura , Eliez Stephan , Stringaris Argyris , Schneider Maude
Published: August 2024

Current psychiatric assessments oversimplify mental health phenomena. Ecological-Momentary-Assessment (EMA) captures richer dynamic interactions between psychological and contextual variables, but the resulting complexity currently hinders clinical translation. Here we propose an innovative approach to integrate dynamic data in clinical practice by accounting for variations within and across symptom clusters over time. We term this approach Behavioral Tractography (BT). We validate BT in independent typically-developing samples and in the clinically-challenging differential diagnosis of psychosis genetic vulnerability in 22q11.2 Deletion Syndrome (22q11DS) and idiopathic Autism Spectrum Disorder (ASD). A novel 2-dimensional rationality/valence structure predicted psychological-contextual fluctuations with striking consistency across typically-developing and clinical samples. Characterizing dynamic interactions between variables within such shared coordinate system, provided an intuitive 3D-view of transdiagnostic and population-specific psychological-contextual pathways. 22q11DS and ASD presented opposite psychological-contextual dynamics, recapitulating Bayesian models of psychosis and autism, and were further differentiated by pathways mediating emergence and consequences of motivational and social wellbeing.
Sailing West: assessing the role of waterways in the Neolithization of Ebro, Po and Rhône basins
Authors: Pirrone Giada , Campus Antonio , Gattiglia Gabriele , Mazzucco Niccolò
Published: August 2024

An unresolved issue within the debates on Neolithization processes concerns the role played by rivers. It is known that farmers and herders were capable of navigating, even over long distances. Still, the question arises to what extent this ability was applied in penetration processes. This research investigates the relationship of early Neolithic farmers with the Ebro, Rhône, and Po rivers. The question underlying the research is to what extent waterways may have played a facilitating or hindering role in the movement from coastal areas to the inland regions of the basins. Predictive, spatial, cost-based, geostatistical, and statistical analyses were employed to answer this question. The initial phase of the research focused on studying the composition of the Neolithic groups in motion. The transported livestock consisted of different species, such as ovicaprids, pigs, and cattle with cattle facing the most difficulties. Therefore, it is likely that the pace of the entire group was adjusted to accommodate the movement of bovids. A movement function based on the characteristics of cattle was developed and integrated with different raster grids to create cost maps representing different scenarios where waterways either hindered or facilitated movement. Subsequently, these scenarios were compared and discussed using statistical analyses, which indicated that in the Ebro basin, rivers likely facilitated Neolithic movement and access to inland points. In the Rhône basin, waterways' roles were variable and less clear. In the Po basin, rivers helped Neolithic groups reach the inner Padana plain, albeit less evidently.
An Efficient Air Quality Detection System Using Sequential Forward Selection- Based ML Algorithms
Authors: Rezk Nermeen Gamal , Sayed Amged , Hemdan Ezz El-Din , El-Behery Heba
Published: August 2024

Air pollution has thus exceeded the anticipated safety limit due to the growing usage of automobiles, the manufacturing sector, and the production of pollutants from other human activities. It is considered one of the major environmental risks to humankind on Earth. Nowadays, monitoring and forecasting air quality is significant, particularly in high-level pollution countries. In contrast to traditional methodologies, predictive technologies based on machine learning approaches be the most effective instruments for analyzing such contemporary threats. Therefore, this paper presents multiclass classification using two feature selection techniques namely Sequential Forward Selection (SFS) and Filter with different Machine Learning and Ensemble techniques to predict the air quality. Therefore, intensive research is conducted in novel techniques such as Wrapper and Filter feature selection methods to make sure that the most relevant features are on datasets for the solution of the air quality problem. The results of the considered framework reveal that the Wrapper feature selection technique provides superior performance compared to various Filter feature selection with different ML methods, including AdaBoost Classifier, Extra Tree Classifier, KNN, RF, GB, and Bagging Classifier for efficiently determining the Air Quality Index (AQI). Its important goal is to visualize the air quality datasets to understand and see the hidden sight in datasets. These models' performances are assessed and compared using predetermined performance metrics. The AdaBoost Classifier model with Filter selection has the lowest accuracy, while the Random Forest Classifier model with Wrapper feature selection achieves the highest accuracy with 78.4% and 99.99% respectively. Based on the raw data set, it was noted that the F1-score, Recall, and Precision values of the Random Forest model Wrapper Feature selection achieve 99.96%, 99.97%, and 99.98% respectively. Therefore, the experimental results undoubtedly show the supremacy of the proposed approach, providing a practical, reliable, and robust tool to effectively determine the Air Quality Index (AQI)
Physiological, biochemical and transcriptomic analyses reveal the mechanism of variation in color traits in Panax japonicus fruits
Authors: Huang Xi Lun , Jin Rui , Tang Ting ting , Liang E , Zhang Lai
Published: August 2024

Panax japonicus C. A. Mey. is a rare and endangered Class II important protected wild medicinal plant in China with a wide range of pharmacological activities. The development of the fruit is special, only the apical capitulum can develop into fruit normally, and the colour trait changes during the maturation process showed a pattern from green to red and from red to purple-black. In order to reveal the phenomenon of colour trait changes during fruit development, this paper analyzed the correlation between colour trait changes and pigment contents (chlorophyll, carotenoids) and secondary metabolite contents (anthocyanosides, flavonoids, and total phenols) of the fruits, and used transcriptome sequencing to explore the correlation between colour trait changes and synthetic genes, and then verified the fluorescence quantification with qRT-PCR. The results showed that chlorophyll was gradually converted and carotenoids began to appear in the pericarp when the fruit entered the colour change stage from the green fruit stage; the content of anthocyanin, flavonoids and total phenolic substances gradually increased during fruit ripening. Transcriptome sequencing obtained transcriptome data of 15 samples from five periods of colour trait changes in Panax japonicus fruits 93.94 Gbp, with 462117 functionally annotated Total Unigenes; the total number of DETs generated by intercomparison of the five periods (G, Y, R, B, P) was 17895 (up-regulated 9435 and down-regulated 8460). Weighted gene co-expression network analysis (WGCNA) indicated that 448 were hub differential genes (DETs) associated with common involvement in the colour changes (carotenoids, anthocyanins, flavonoids, total phenols) in the fruits of Duchess. GO and KEGG were enriched to participate in the photosynthesis - antenna protein pathway 19; involved in flavonoid biosynthesis a total of 205. The results of qRT-PCR fluorescence quantitative validation showed that chlorophyll degradation related 6 candidate genes PjCAB and fruit colour change flavonoid biosynthesis 6 candidate genes PjF3'H, PjCHI, PjCHS, PjDFR, PjANS, and PjC3'H at five periods were consistent with the transcriptome sequencing results.