bluuebunny/crossref_metadata_2025_split huggingface dataset:
Statistical optimization of process variables for improved Polyethylene terephthalate plastic degradation by a rhizospheric bacterial consortium
Authors: Dhaka Vaishali , Singh Simranjeet , Rao Raman , Garg Shashank , Samuel Jastin , Khan Nadeem A , RAMAMURTHY PRAVEEN C , Singh Joginder 
Published: September 2024

Abstract

The current study focuses on the polyethylene terephthalate (PET) powder degradation potential of a rhizobacterial consortium screened from the rhizosphere of plants growing at plastic-polluted sites. The rhizobacterial isolates were screened, and the ability of PET powder degradation was studied for up to 18 days. For observing the efficiency of degradation, all three rhizobacterial strains with the highest percentage of degradation were combined to formulate the consortium. The Response Surface Methodology was used to optimize the process variables. The combinations demonstrating the highest weight reduction percentage for PET were selected for further degradation studies. The changes in the structure and surfaces that occurred after biodegradation on the plastic were observed through SEM and FTIR analysis. The obtained results showed the disappearance and elongation of the peak, signifying that the rhizobacterial consortium could modify the PET plastic. The weight reduction percentage of PET powder (300 µm) was 71.12% at optimized conditions (29.8ºC, 7.02 pH and 1g/L carbon source). The mathematical model developed through RSM is found to be significant (P < 0.05), and optimization and validation experiments were also well correlated for the process.
Rolling Bearing Fault Diagnosis Method Based on Multi-scale Convolutional Neural Network with Selective Kernel Attention Mechanism
Authors: Zhao Shuping , Liu Xilong , Liang Changyong , Lu Wenxing , Cui Yong 
Published: September 2024

Abstract

Rolling bearings, as core components of rotating machinery, require timely and accurate identification of fault types to ensure the safe and stable operation of mechanical equipment. However, existing fault diagnosis techniques for rolling bearings face challenges in terms of comprehensive feature extraction and noise resistance. To address these issues, this paper proposes a fault diagnosis method based on a multi-scale convolutional neural network (MSCNN) integrated with a selective kernel attention mechanism. First, a MSCNN is constructed as the feature learning framework. It employs dilated convolutional kernels to capture fault features across multiple frequencies and incorporates batch normalization layers to mitigate overfitting. Second, the selective kernel attention mechanism is enhanced with adaptive max pooling, enabling the dynamic adjustment of pooling region sizes to effectively reduce information redundancy. Experimental validation using two bearing datasets demonstrates that the proposed method outperforms existing techniques in terms of fault diagnosis accuracy, robustness, and generalization capability.
The effect of emersion and UV solar radiation on Pacific oyster Crassostrea gigas survival and pathogen development in the intertidal environment.
Authors: Lynch Sharon , Kett Gary , Jansen Marcel , Culloty Sarah 
Published: September 2024

Abstract

Pacific oysters Crassostrea gigas are cultured intertidally in estuaries and bays and are prone to disease outbreaks associated with pathogens (ostreid herpesvirus-1 microVar (OsHV-1 mVar) and Vibrio bacteria), which can decimate stocks. The holding height on the intertidal exposes C. gigas to various biotic and abiotic factors for e.g. UV radiation which has poorly known impacts on oyster survival and pathogen development. A 5-month field trial was carried out at two shore heights (2 m vertical differential) to investigate young C. gigas (spat) survival and pathogen development. UV exposure, tidal height and air temperature were recorded. 1000 oyster spat were divided equally between two shore heights (HS and LS) and sampled weekly. Mortality was counted in situ and pathogen screening for V. aestuarianus and OsHV-1 mVar was carried out by PCR and qPCR on (n = 570) C. gigas. Results indicate that higher oyster mortality was positively associated with emersion duration, including UV exposure (>2.4 kJ/m2) and high air temperatures (>21 oC). Pathogen partitioning was observed i.e. a higher prevalence of OsHV-1 mVar in HS C. gigas while a higher prevalence of V. aestuarianus was detected in LS C. gigas, also reflected in infection intensity. This study shows that oyster spat mortality and pathogen infection levels are influenced by the growing height on the shore above Chart Datum. Data are supported by and contrasted to previous studies. These findings are especially relevant to global coastal aquaculture sites experiencing summer mass mortality episodes and outbreaks of Vibrio and/or herpesvirus related diseases.
A Discrete Physical Model for Analyzing the Vibrations of a Non-Uniform Bi-Directional FGM Beam under Elastic Foundations and Different Support Conditions
Authors: Moukhliss Anass , Rahmouni Abdellatif , Benamar Rhali 
Published: September 2024

Abstract

This study employs a discrete physical model (DPM) to investigate the small-amplitude transverse free vibrations of non-uniform beams made from bidirectional functionally graded materials (2D-FGM), the material properties of the beam are varied continuously in both the axial and transverse directions by exponential gradation laws. The beam is analyzed on variable elastic foundations and under various boundary conditions. The model represents the continuous beam as a multi-degree-of-freedom (MDOF) system that incorporates masses, bars, and spiral linear springs. After calculating the system's mass and linear stiffness matrices, as well as the foundation's rigidity matrix, which are computed using an appropriate discretization that aligns with the properties of the examined beam, Hamilton's principle is applied to derive a set of algebraic equations predicting the non-dimensional natural frequencies and mode shapes of the beams. The numerical results obtained from this discrete model were compared with those from previous studies to validate the proposed approach. The flexibility of this model allows for precise adjustment of linear vibration frequencies by modifying the geometrical properties of the beams, the gradation exponents in the $x$ and $y$ directions $(n_x, n_y)$, the taper ratio $\gamma$ of the non-uniform beam, and the foundation's position $\chi$ and intensity $\eta$, as well as the boundary conditions. This highlights its utility in analyzing and designing complex beam structures for diverse engineering applications.
Femtosecond laser drilling controlled with laser-generated ultrasound pressure
Authors: HAYASAKI YOSHIO , MIURA TAKUMA 
Published: September 2024

Abstract

Laser drilling of glass using tightly focused femtosecond laser pulses while monitoring laser-generated sound is demonstrated, aiming laser drilling controlled by laser-generated sound. The amount of laser ablation was found to have a monotonical relation to the intensity of the sound pressure. It was also found that when the laser pulses were focused on the glass surface, the sound pressure increased in the initial stage of the laser drilling and then declined as the hole became deeper. These behaviors were the result of increasing ablation caused by surface roughening and loss of sound propagation through the hole, respectively. It was further found that the movement of the objective lens (OL) toward the target material at an appropriate constant speed created a hole with a large depth and narrow entrance (a high aspect ratio); that is, the lens movement changed the performance of the laser drilling. A simple method for moving the lens using laser-generated sound was adopted in this study. The axial position of the OL was controlled by maximizing the sound pressure at each pulse irradiation to obtain a hole with a high aspect ratio, which was the same as the maximum hole depth obtained by the iterative experiments in the constant-speed control of the OL. More sophisticated control methods should be developed according to the given applications.
Interplay between structural integrity and aromaticity on governing the nature of the non- covalent interactions within the mono and di-solvent clusters of 2-Hydroxypyridine and 2- Hydroxynicotionic acid: A topological description
Authors: Ganguly Aniruddha 
Published: September 2024

Abstract

Bader’s “Atoms in Molecules” formalism has been adopted to assess the non-covalent interactions present within the mono and di-solvent (water and methanol) clusters of 2-Hydroxypyridine and 2-Hydroxynicotionic acid in their Closed and Open conformations and to critically analyze the characteristics and the energetics of the interaction lines towards the planarity of the structural skeletons. Nucleus independent chemical shift (NICS) descriptor has also been exploited to delineate the role of aromaticity in dictating the structures and the characteristics of the non-covalent interactions present within the studied compounds. Both electrostatic and partially covalent Hydrogen bonding interactions (HB) are found within the clusters. Furthermore, apart from the typical O····H–O and N····H–O HBs, a weak albeit unique O····H–C interaction line of purely electrostatic origin is observed. The covalency of the HBs as well as the structural constraints are found to modulate the aromaticity of the associated pyridine nuclei.
Determinants of Retroplacental Hematoma at the Maradi Mother and Child Health Center, Niger: a case‒control
Authors: Ali. Zaratou 
Published: September 2024

Abstract

Introduction
Retroplacental hematoma is a paroxysmal accident that threatens maternal and fetal prognosis. It is a major emergency in obstetric pathology. The objective of this study was to identify the factors associated with retroplacental hematoma at the Maradi Mother and Child Health Center in 2022.
Methods
This was a case‒control cross-sectional analytical study that used patient records for the year 2022 from September 20 to October 20, 2023. The presence of retroplacental hematoma was the outcome variable and was measured by a case (yes) or control (no) response. The exposure variables included sociodemographic characteristics, obstetric characteristics, care, progression of patients and neonatal characteristics. Pearson's chi-square tests at the 5% significance level were used to analyze differences between categorical variables. All variables that had a bilateral p value <0.05 in the bivariate analysis were introduced into the binary logistic regression model to identify factors associated with retroplacental hematoma.
Results
A total of 246 cases of retroplacental hematoma were recorded out of 4731 deliveries recorded during the study period, for an estimated frequency of 5.20%. The mean age of the patients was 29.41 ± 6.94 years. Factors associated with retroplacental hematoma included pauci-multiparity (2 more children) [adjusted odds ratio (ORA): 1.57, 95% confidence interval (CI) (1.01-2.23)], fewer than 4 antenatal visits [AOR: 10.70, 95% CI (1.14-99.74)], blood transfusion [AOR: 2.01, 95% CI (1.11-3.60)], a newborn birth weight less than 2500 grams [AOR: 1.92, 95% CI (1.53-2.42)] and fetal mortality in utero [AOR: 13.20, 95% CI (1.86-93.70)].
Conclusion: This study identified the factors associated with retroplacental hematoma. Prevention requires regular, high-quality prenatal care. Early diagnosis and cesarean section improve maternal–fetal prognosis.
Dielectric Relaxation Studies of Eu3+ Doped Graphene Oxide Nano Layers
Authors: I DHANYA , ABRAHAM NIKHILA ANN , PISHARADY SREEJITH K 
Published: September 2024

Abstract

A bulk amount of Graphene Oxide nanosheets is prepared using the Modified Hummers’ Method. Rare earth material such as Europium nitrate pentahydrate compound is added to graphene oxide in varying percentages to study the dielectric behaviour of graphene oxide. Morphological analysis results reveal a nano sheet-like pattern in pure graphene oxide, while for the Europium-doped graphene oxide, a cluster of Europium atoms seems trapped between layers of graphene. The electron diffraction rings are indexed using multiphase analysis, and the hexagonal carbon structure remains unaltered in doped samples. Electrochemical Impedance Spectroscopy (EIS) studies are conducted on pure and Europium-doped graphene oxide. Frequency variations with the real and imaginary parts of dielectric constants are studied for both the composite material and the pure graphene oxide. Also performed are Photoluminescence (PL) studies. The emission spectrum of Eu3+ doped Graphene oxide is used to study the Judd-Ofelt parameters and allowed transition probability is determined.
Industrial Big Data-Enabled Deep Learning: Integrating AI-Driven Adaptive Attention with LSTM for Advanced Solar Photovoltaic Power Forecasting
Authors: Li Shuai 
Published: September 2024

Abstract

The escalating global deployment of Solar Photovoltaic (PV) systems highlights an urgent demand for sophisticated power output forecasting methods that leverage the vast datasets characteristic of industrial applications. Precise forecasting is essential for maintaining grid stability, optimizing energy distribution, and balancing the supply-demand equation, particularly given the unpredictable nature of solar energy sources. Long Short-Term Memory (LSTM) networks, renowned for their proficiency in capturing long-term dependencies within time-series data, have emerged as a leading solution to this forecasting challenge. However, the static attention mechanisms in traditional LSTM models are ill-equipped to handle the complex dynamics of solar power data.
This paper introduces an innovative LSTM model that integrates an AI-driven adaptive attention mechanism, designed to harness the power of industrial big data for enhanced forecasting. The model dynamically identifies and emphasizes relevant temporal features, thereby increasing its responsiveness to real-time data fluctuations. Our approach, after extensive validation using a diverse set of benchmark solar PV datasets, demonstrates a remarkable improvement in forecasting accuracy over conventional LSTM models.
The adaptive attention mechanism confers a twofold benefit: it enhances the model's adaptability by adjusting its focus in accordance with shifting data patterns, and it promotes interpretability by clarifying which temporal features are considered most influential by the model at any given moment. Ultimately, the integration of adaptive attention with LSTM establishes a new precedent in solar PV power forecasting and suggests broader applications across the renewable energy sector, showcasing the model's adaptability and wide-ranging potential.
Enhancing Clonal Micropropagation of Zarya Alatau Apple
Authors: Yerbolova Laura S. , Rakhatkyzy Akbota , Aubakirova Karlygash P. , Bakytzhanova Zhibek N. , Kryldakov Ruslan V. , Galiakparov Nurbol N. 
Published: September 2024

The purpose of this study was to improve the protocol of clonal micropropagation for effective mass production of the Zarya Alatau apple cultivar through the use of axillary buds. In Kazakhstan’s challenging climate, the Zarya Alatau apple thrives because of its unique traits, including fruit preservation until May, cold hardiness, and resistance to scab and powdery mildew. Micropropagation is essential for healthy mother tree establishment, and this research focused on key factors for successful in vitro propagation. The sterilization of explants was optimized: 1.6% solution of sodium hypochlorite effectively sterilized plant materials for 10 minutes. Nutrient media composition was evaluated for efficient shoot regeneration. The study examined axillary bud regeneration on Murashige and Skoog medium with different concentrations of hormones. A combination of 6-benzylaminopurine (0.5 mg/L) and gibberellic acid (0.5 mg/L) yielded optimal results, with shoots reaching 3.5 cm. Root induction was analyzed with varying indole-3-acetic acid (IAA) concentrations, and the best results were achieved with 1.5 mg/L IAA, resulting in an 85% rooting frequency. Adapting in vitro plants to ex vitro conditions is crucial given their sensitivity to environmental changes. Well-developed leaves and a robust root system are essential for successful acclimatization during transplantation into a soil substrate. This research provides valuable insights into the critical parameters for a successful transition of in vitro propagated plants to soil conditions, optimizing micropropagation practices.
Study on terrain response of the military mobile repair vehicle towing power generator trailer before and after improvement
Authors: Dao Quyen Manh , Tran Thang Duc , Le Duong Van 
Published: September 2024

Mobile repair vehicles play an indispensable role on the battlefield and are increasingly being improved to enhance their effectiveness. When moving to repair locations on the battlefield, they often tow trailers, which include power generator sets. In some cases, these generator sets are replaced by trailers to transport ammunition or carry wounded soldiers. The article proposes improvements to the suspension system on the generator trailers and discusses the impact of vehicle speed and random road roughness on the movement of the mobile repair vehicle-trailer combination before and after the improvements. A dynamic model of the multi-body system is constructed, with the towing vehicle being a three-axle truck. The random roughness profile of the road surface is determined from simulation results based on ISO 8068 standards. The equations of motion are established using Lagrange's method and solved through simulation using Matlab software. The results of the article indicate the oscillation of the mobile repair vehicle-trailer combination when traveling at speeds of 36 km/h and 54 km/h on road surfaces with random roughness levels of class D and class E. After the improvement of the suspension system on the generator trailers, smoother trailer motion is observed. The study has shown that the vertical oscillation amplitude of the trailer decreased by up to 18 %, while the oscillation speed decreased by as much as 40 %. The findings provide a basis for further improving the suspension system on generator trailers to minimize oscillations, which is crucial for replacing generator trailers with specialized trailers for transporting ammunition or wounded soldiers on the battlefield. This is a significant issue in the field of national security and defense
Effective Strategies for Boosting Critical Thinking and Learning Motivation: The PQ4R Approach
Authors: Lutfianasari Ulfa , Nasikah Ilmi 
Published: September 2024

This research aims to determine the effectiveness of the PQ4R learning strategy on students' critical thinking skills and learning motivation. This research uses quasi-experimental research with a nonequivalent control group design. The population in this study was part of class XI MIPA at MA Negeri Kendal. Sampling was carried out using the cluster random sampling technique. The sample used in this research was 36 students of class XI MIPA 4 as the experimental class and 32 students of class XI MIPA 3 as the control class. The research results showed that the critical thinking skills t-test obtained a significance value (Sig.) 0.000 0.05, meaning there were differences in critical thinking skills between the experimental and control classes. Based on the results of the N-Gain test, critical thinking skills for the experimental class were 0.4418, and for the control class were 0.1483. The results of the t-test research on learning motivation obtained a significance value (Sig.) 0.001 0.05, meaning there is a difference in learning motivation for the experimental and control classes. Based on the results of the N-Gain test, the learning motivation for the experimental class was 0.3315, and the control class was 0.1529. This research concludes that the effect of the effectiveness of using the PQ4R learning strategy on critical thinking skills and learning motivation in the experimental class is higher than in the control class.
The Effect of Kinesio Taping on Diastasis Rectus Abdominal in Postpartum: A Systematic Review and Meta-analysis
Authors: Salekzamani Yaghoob , Moradian Mohsen , Eftekharsadat Bina , Mirghafourvand Mojgan , Hasanpour Shirin , Asghari Kimia Motlagh , Bani Soheila 
Published: September 2024

Background:
During pregnancy, hormonal and physiological changes can affect the abdominal
muscles. Diastasis rectus abdominis can often be detected during pregnancy and the postpartum
period.

Objective:
The aim of this study was to determine the effect of kinesio taping on rectus abdominis
diastasis in the postpartum period.

Methods:
In this study, all published RCTs and quasi-RCT studies related to the studied title were
searched and evaluated by considering the PICO method in PubMed, Web of Science, and Scopus
until September 2022. Meta-analysis was performed using Review Manager 5.3 statistical software.
Initially, 146 articles were analyzed, and after duplicates had been removed, 109 articles were
available for evaluation. Finally, seven studies were included in the meta-analysis.

Results:
The outcome of the meta-analysis showed a statistically significant difference in improving
intra rectus Diastasis above the umbilical (MD: -0.24 (95% CI: -0.33, -0.16; P < 0.00001, I2 =
89%), but at the level and below the umbilical, the results were not significant. In this study, the results
of this meta-analysis using the random effects model showed a statistically significant difference
between the intervention group receiving kinesio taping and the control group (MD: -0.51;
95%) regarding physical disability due to back pain. CI: -1.86, -1.16, P = 0.00001, I2 = 0%.

Conclusions:
Kinesio taping alone or in combination with exercise improves DRA (more significant
above the umbilicus), physical disability due to low back, and decreased abdominal circumference
size in postpartum better than other methods.