bluuebunny/crossref_metadata_2025_split huggingface dataset:
Based on the 4D Label-free protein qualitative analysis method and coomassie brilliant blue method quantitative determination of protein content to improve the quality standards of Xiangdan injection
Authors: Xu Min , Ye Zhangkai , Chen Yuchen , Cai Jia , Zhu Shunpeng , Yang Qiang , Wen GuoLiang , Huang Ruizhen , Zhang Liang , Ye Qiang 
Published: June 2024

Abstract

Xiangdan injection (XDI), as a common Chinese medicine injection (CMIs), is mainly used clinically to activate blood circulation, relieve blood congestion and dilate coronary arteries. However, allergic reactions occasionally occurred during the use of XDI, which could be related to the protein in XDI. Therefore, we conducted research on the commercial XDI and tested it according to the requirements of the Chinese Pharmacopoeia for CMIs. Firstly, 4D-Label-free quantitative proteomics technique was used to identify the samples of XDI and Salvia miltiorrhiza (SM), eleven identical proteins were found. The results indicated that XDI contained trace proteins which come from SM with a molecular weight range of 15-181KD. Then the qualitative experiments about proteins were carried out via the sulfosalicylic acid (SA) method and the tannic acid (TA) method, which were required in the Chinese pharmacopoeia. To our surprise, the qualitative experiments in the Chinese pharmacopoeia could not precise identify the proteins in XDI. Unexpectedly, the reason is that the excipient Tween 80 in XDI would cause a false-positive reaction. Therefore the proteins in XDI were inspected qualitatively and quantitatively after eliminating false-positive reactions. The protein content in XDI was determined by coomassie brilliant blue method. It was discovered that the protein concentration was 3.038 mg/ml, which would not generate a positive reaction. Finally the combination of qualitative and quantitative protein experiments provide an exclusive identification method for XDI, which could promote the quanlity standards of XDI and guarantee the clinic safety.
Combustion and mechanical property enhancement strategy based on SA surface activated boron powders
Authors: Lu Jiaxin , Chen Chong , Zhang Bobo , Niu Kang , Xiao Fei , Liang Taixin 
Published: June 2024

Abstract

Boric acid and other impurities on the surface of boron (B) particles can interact with hydroxyl-terminated polybutadiene (HTPB), which can weak the mechanical properties and energy release efficiency of boron-based solid rocket propellants. In this paper, solvent evaporation induced self-assembly was used to coat the surface of B particles with stearic acid (SA) and the SA@B composite particles were prepared. The effects of SA coating on the combustion performance of B particles and the mechanical properties of HTPB matrix composites were investigated. The results showed that the SA coating enhanced the oxidation efficiency of B particles in air. The heat of combustion value of the SA@B composite particles, reached up to 30.29 MJ/g. During the combustion of SA@B composite particles, there are fewer molten solid particles surrounding the flame, which enhances the stability of B particles combustion process. Furthermore, the SA coating effectively enhanced the dispersion of B particles in HTPB. At a stretching speed of 100 mm/min, the tensile strength of the SA@B/HTPB composite materials is higher than that of the B/HTPB composite materials. Moreover, when the mass loading of the SA@B composite particles reaches 50 wt%, the tensile strength of SA@B/HTPB composite materials achieves 0.63 MPa. The compatibility between B particles and HTPB can be effectively improved by surface-activated B particles with SA, which is of great significance for the storage stability of boron-based solid rocket propellants.
Investigation of vibration dynamics and failure prediction of ball bearing in two rotor system: Qualitative and Quantitative approach
Authors: Duraisamy prakash , kumarasamy Suresh , Rajagopal Karthikeyan , Karthikeyan Anitha 
Published: June 2024

Abstract

The study investigates the vibration dynamics and failure prediction of ball bearings under common failure scenarios. The experiments involve normal bearings, faulty bearings, and conditions involving external rubbing. Various analyses such as time series analysis, Fast Fourier Transform, recurrence analysis, and the Dragon-King test are employed for the classification of different vibrations created in the system. These analyses aim to assess the condition of faulty bearings and detect any anomalies or extreme events. The complementary cumulative distribution function (CCDF) proves to be an effective method for identifying outliers in temporal data, providing the probability of events in the time series. The CCDF plot is specifically utilized to reveal the probability of a dragon-king extreme event in the case of rubbing. Extracting essential recurrence metrics from Recurrence Plots, such as recurrence rate, mean recurrence time, recurrence time entropy, laminarity, and determinism, allows for a quantitative understanding of the system's behavior. The study contributes valuable insights into the vibrational characteristics of ball bearings and offers a robust methodology for predicting failures and identifying abnormal events in complex mechanical systems.
Fourier PD and PDUNet: Complex-valued networks to speed-up MR Thermometry during Hyperthermia
Authors: Khatun Rupali , Chatterjee Soumick , Bert Christoph , Wadepohl Martin , Ott Oliver J. , Semrau Sabine , Fietkau Rainer , Nürnberger Andreas , Gaipl Udo S. , Frey Benjamin 
Published: June 2024

Abstract

Hyperthermia (HT) in combination with radio-and/or chemotherapy has become an accepted cancer treatment for distinct solid tumour entities. In HT, tumour tissue is exogenously heated to temperatures of 39 to 43 °C for 60 minutes. Temperature monitoring can be performed noninvasively using dynamic magnetic resonance imaging (MRI). However, the slow nature of MRI leads to motion artefacts in the images due to the movements of patients during image acquisition time. By discarding parts of the data, the speed of the acquisition can be increased-known as Undersampling. However, due to the invalidation of the Nyquist criterion, the acquired images have lower resolution and can also produce artefacts. The aim of this work was, therefore, to reconstruct highly undersampled MR thermometry acquisitions with better resolution and with less artefacts compared to conventional techniques like compressed sensing. The use of deep learning in the medical field has emerged in recent times, and various studies have shown that deep learning has the potential to solve inverse problems such as MR image reconstruction. However, most of the published work only focusses on the magnitude images, while the phase images are ignored, which are fundamental requirements for MR thermometry. This work, for the first time ever, presents deep learning based solutions for reconstructing undersampled MR thermometry data. Two different deep learning models have been employed here, the Fourier Primal-Dual network and Fourier Primal-Dual UNet, to reconstruct highly undersampled complex images of MR thermometry. MR images of 44 patients with different sarcoma cancers who have received the HT treatment in a combination of radiotherapy/chemotherapy were used in this study. It was observed that the method was able to reduce the temperature difference between the undersampled MRIs and the fully sampled MRIs from 1.5 °C to 0.5°C.
The effect of 6 weeks of high intensity interval training (HIIT) on expression of mirRNA29-c and mirRNA146-a in the hippocampus of streptozotocin- induced diabetic male rats
Authors: Ichi Mehdi Soltani , Shabkhiz Fatemeh , Kordi Mohammadreza 
Published: June 2024

Abstract

Background/objectives:
MicroRNAs have been reported as potentially useful biomarkers for various diseases, including diabetes, heart diseases, and neurological diseases. The aim of this study was to assess whether microRNA-146a and its inflammatory mediator (TNF-a) and microRNA-29c may be changed in the hippocampus of streptozotocin-induced diabetic rats, after a period of high – intensity interval training.
Methods
Twenty-four male Wistar rats (180 ± 10 g, 8–10 weeks age) were assigned to 4 groups: control (C), diabetes (D-1w), diabetes (D-6w), and diabetes high-intensity interval training (DHIIT). Diabetes induced by the single-dose injection of streptozotocin (STZ; 55 mg/kg dissolved in 0.1 M of citrate buffer; pH 4.5; i.p.) in 12-h fasted and blood sugar higher than 250 was considered diabetic. The effects of six weeks of HIIT on hippocampus microRNA-146a, microRNA-29c, as well as evaluation of tumor necrosis factor-alpha (TNF-α ) in serum were evaluated using Real-Time PCR and ELISA techniques respectively.
Results
The results indicated a reduction in expression of miR-146a and an increase in expression of microRNA-29c genes in the hippocampus of diabetic rats compared to control. Also TNFα increased in the D groups in comparison with C group. However, HIIT training in DHIIT significantly decreased the microRNA-29c and TNFα and increased microRNA-146a expression in comparison of D-6w group.
Conclusion
Our results implied that increased hyperglycemia and inflammation status were associated with brain impairment in DM rats, which were negatively correlated with miR-146a and microRNA-29c expression. It seems that HIIT training improves hypoglycemic and inflammatory conditions in diabetic rats.
What are the perceptions and lived experiences of Canadian injured workers about the provision of physiotherapy services using telerehabilitation?
Authors: Hudon Anne , Miciak Maxi , Slade Teri , Lovo Stacey , Whittaker Jackie L. , Côté Daniel , Feldman Debbie E. , Kairy Dahlia , Laberge Marie , McKeen Beverley , Cooper Lynn , Gross Douglas 
Published: June 2024

Abstract

Purpose
Despite evidence of efficacy, the effectiveness of telerehabilitation in real-world clinical settings is still largely unknown. Telerehabilitation requires a substantial transformation of the organization and delivery of traditional services. Considering that a virtual setting can create unique challenges for providing physiotherapy services and given the physical and potential hands-on nature of evidence-based assessments and interventions, it is important to investigate what injured workers think of receiving physiotherapy care via telerehabilitation and to examine if rehabilitation needs are adequately met.
Methods
A qualitative interpretive description study was conducted to explore the perspectives and experiences of 17 injured workers receiving physiotherapy via telerehabilitation. Data were collected through semi-structured interviews with participants from three provinces in Western Canada and analysed using thematic analysis.
Results
Implementation of telerehabilitation during the COVID-19 pandemic resulted in mixed perceptions from injured workers. Some viewed telerehabilitation as a resourceful option for providing services during the pandemic lockdown, resulting in maintained communications while overcoming barriers to services (e.g., rural/remote workers, transportation barriers, etc.). However, many thought telerehabilitation was inferior to in-person therapy for assessment and when ‘hands-on’ interaction was needed. Many believed a hybrid option may be ideal now that pandemic restrictions are lifted, with telerehabilitation supplementing in-person physiotherapy when needed.
Conclusions
Telerehabilitation was viewed as a resourceful option during the pandemic and in certain clinical situations (e.g., rural/remote). Workers should be able to make informed choices about service delivery format.
A Study on the Consumer Satisfaction Towards Mobile Banking Services of State Bank of India- With Special Reference to Dharamshala
Authors: Dhiman Indu Dhiman Indu , Sharma Puneeta Sharma Dr. Puneeta 
Published: June 2024

Abstract

The banking industry and its customers have benefited greatly from recent telecommunications innovations. One such innovation is mobile banking, which allows customers to communicate with banks via cell phones and receive services like account information, fund transfers, short message services, check book issuance, and more. Mobile banking is a significant and developing method of carrying out financial operations. Currently, practically every bank in the globe offers "Mobile Banking" services to its customers. This research aims to investigate the Preference level of customers for Mobile Banking Services and the satisfaction level of customers towards Mobile Banking Services of SBI. This study is conducted in Dharamshala and customers using Mobile-banking service in State Bank of India (SBI).The present study has been collected from primary data on the basis of issue questionnaire, the sample size for study was only 81 mobile banking users of SBI.
Inflation Reduction Act incentives increase cost-competitiveness of lower-footprint clean hydrogen-based sustainable aviation fuel
Authors: Phadke Amol , Bennett Jose Luis Dominguez , Popovich Natalie , Paliwal Umed 
Published: June 2024

Abstract

This study demonstrates that the US 2022 Inflation Reduction Act (IRA) provides a pathway to lower the cost of producing sustainable aviation fuel (SAF) by up to a third, making it cost-competitive with conventional jet fuel. We investigate three hydrogen-intensive electrofuel pathways—i.e., using carbon from biomass, point source emissions, and direct air capture (DAC)—for all contiguous US counties. In particular, the SAF production pathway using hydrogen produced from off-grid renewables and carbon from biomass offers several promising benefits, namely a 2.5-fold increase in biomass efficiency; 60% and 58% decreases in water and land use, respectively; and 93% and above-99% carbon emissions reductions compared to biomass-based SAF strategies and fossil jet fuel, respectively. This approach requires an average of only 4% of counties’ renewable electricity potential to meet 2050 SAF production targets. Consequently, we suggest stakeholders develop a revised strategy to significantly scale US deployment of economically viable SAF that leverages low-cost clean hydrogen supply enabled by the high-quality renewable potential and long-lasting IRA incentives.
Two-beam Interference Microscopy: high-resolution multi-scale light-sheet imaging from subcellular structures to whole organs
Authors: Fei Peng , Zhou Yao , Guo Xinyi , Mao Shiqi , Liu Jianchao , Zhang Meng , Li Mengmeng , Zhu Jingtan , Yi Yating , Ye Chaoliang , Ma Yifan , Yang Qihang , Wang Zhaofei , Si Wentian , Fang Yuekun , Li Dongyu , Chen Liting , Jiang Man , Zhao Hu , Yu Tingting , Zhu Dan , Kuang Dong , Wang Guoping , Zhang Yu-Hui 
Published: June 2024

Abstract

Despite offering rapid and gentle 3D imaging of biological samples, the revolution by light-sheet fluorescence microscopy faces challenges due to optical constraints and limited geometry flexibility, hindering its widespread application. Here we present Two-beam Interference Microscopy (TIM), which sweeps the interference pattern of two symmetric laser sheets to achieve horizontal plane illumination and orthogonal wide-field detection for the first time using a single objective. The geometry-unconstrained TIM yields adaptive optical sectioning of samples with various sizes and mounting approaches. It enables high-speed (over 150 megavoxels/s), adaptive-resolution (~200 nm to ~2500 nm), nanoscale-to-mesoscale 3D imaging ranging from single organelles within a live cell (×100), to a whole mouse brain containing tens of millions of neurons (×4 tile stitching). TIM exhibits remarkably high versatility while achieving superior spatiotemporal resolution. With feedback-controlled imaging strategies, intelligent TIM demonstrates in situ trans-scale visualization from entire brain slices to single dendritic spines, and efficient event-triggered imaging of CAR-T/tumor cells’ cytotoxic interactions.
Proposed Student Learning Model in a Hybrid Learning Environment
Authors: Osajiuba Ojoma , Pardede Eric , Tomy Sarath 
Published: June 2024

Abstract

Hybrid learning has become a new norm in higher education institutions, particularly since the COVID-19 pandemic. The hybrid learning environment is faced with many challenges and issues. The motivation for this study is to further substantiate this potential new normal by exploring strategies to address the challenges faced by students in the new learning environment. A learning model was proposed as a strategy for tailoring learning activities according to individual preferences to achieve optimal productivity. Although there are many existing learning strategies and styles, there is a need to propose a model that accommodates student engagement online and, in the classroom, simultaneously. The proposed learning model is formulated to harness the advantages and address the challenges faced by students in hybrid learning environments. The proposed model is called the AIMS (agile, intermittent, meteoric and self-pace) learning model and consists of six characteristic features (study habit/skills, study medium, class participation, learning environment, teaching method format, and assessment preference). The characteristic features were identified from the literature and from several existing learning style models to form the basis for the AIMS learning model. Proposing this learning model is necessary to address the challenges students face in hybrid learning environments, and addressing these challenges can lead to the development of tailored learning and teaching strategies that cater to diverse learning styles, thereby improving the overall learning experience of students. These improved practices positively affect academic performance and can help in the development of tools and platforms that better cater to the diverse learning styles of students. Universities can help distribute resources more effectively, and academics/educators can benefit from these research findings by gaining insights into effective pedagogical approaches to ensuring an optimized learning environment.
Factors Influencing Suicidal Thoughts in Rural Tamil Nadu Adolescents
Authors: R Anjit Raja , B Nagarajan 
Published: June 2024

Abstract

Suicide is a pressing public health issue among adolescents globally, particularly in low- and middle-income regions like Tamil Nadu. Despite ample evidence from developed nations linking suicidal ideation (SI) in adolescents to social and individual factors, research from low- and middle-income countries is limited. This study is the first to explore SI prevalence and its social determinants among rural Tamil Nadu adolescents, focusing on socioeconomic status (SES). Drawing from two studies conducted in 2023, involving 4,598 adolescents aged 13-19, this paper utilized data from a cross-sectional survey in a rural Tamil Nadu community. Results from Study - I revealed a lifetime SI prevalence of 14%, with a significant proportion being female (68%), unmarried (5.8%), and students (6.4%). SI was notably associated with age, education, occupation, and living arrangements. Adolescents aged 17-19, with SSC/HSC education, day laborers, and those not living with parents showed elevated odds ratios for SI. SI prevalence was higher among adolescents from low-income families, with parental education, marital status, and house ownership significantly influencing SI odds. Adolescents with single parents and those with parents having lower education levels exhibited higher SI odds. However, adolescents from households owning a house had lower SI odds.This research underscores a moderately high prevalence of SI among rural Tamil Nadu adolescents. It highlights the significant influence of personal and familial characteristics, even after adjusting for potential confounders.
Understanding these factors is crucial for developing effective interventions to address adolescent suicidal ideation in low-resource settings.
Natural aliphatic lipids and sterols in sediments from Obhur Lagoon, Red Sea coast of Saudi Arabia: Concentrations, spatial distributions, and sources
Authors: Rushdi Ahmed I. , Alharbi Hattan A. , Rasul Najeeb , Bazeyad Abdulqader , Simoneit Bernd R. T. , Goni Miguel A. , Al-Mutlaq Khalid F. 
Published: June 2024

Abstract

Samples from the upper surface sediments of Obhur Lagoon - north Jeddah were collected to determine the concentrations, spatial distribution, and sources of natural lipids. The lagoon was divided into three zones based on their immediate ecosystems: Z I (adjoining inland), Z II (the region between Z I and the adjacent coastal Z III), and Z III (coastal region). The major natural biogenic lipid compounds of the total extractable organic matter (TEOM) were n-alkanes (partial), fatty acids, fatty alcohols, and steroids.
The n-alkanes of biogenic sources were mainly from terrestrial higher plant wax and decreased from about 38% to 12% from Z I to Z III. Their aquatic algal and diatom sources increased from ~ 1% to 8% for Z I to Z III and microbial inputs decreased from ~ 3% to 0.5% for Z I to Z III. Relative concentrations of fatty acid inputs from higher plants varied from ~ 6% in Z I, 4% in Z II, and 5% in Z III; from aquatic algae sources ~ 80% in all regions; and from microbes ~14-12% with a slight decrease from Z I to Z III. The terrestrial input of fatty n-alcohols decreased from ~ 32% to 11% for Z I to Z III, from ~ 62% to 45% in Z I to Z III from aquatic algae and diatom sources, whereas microbial inputs varied around 10%. Steroid inputs from terrestrial plants were in decreasing order from Z I (37%) to Z III (16%), whilst from the aquatic biota, they increased from Z I (58%) to Z III (76%). The microbial inputs of steroids were in the order of Z III (11.5%) > Z II (9.9%) > Z I (9.4%).
The contributions of the total natural lipids from terrestrial sources decreased from Z I (42.8%) to Z III (19.2%), whereas the aquatic source component increased from Z I (53.0%) to Z III (77.4%). The results indicate that the lagoon biogeochemistry is influenced by the immediate ecosystems, hydrodynamic of the lagoon, and human and social activities in the area.