bluuebunny/crossref_metadata_2025_split huggingface dataset:
Measurement and analysis of health productivity in China——Based on the perspective of the "Regional Differentiation Study"
Authors: Kong Dechen , Jiang Nan , He Xiaomin , Yuan Jing , Du Qing , Lian Wu 
Published: July 2024

Abstract

Background
Chinese mainland includes 31 provinces, autonomous regions, and municipalities directly under the central government (referred to collectively as provinces for simplicity). There are still a lot of problems in China's medical system, such as regional imbalance, outstanding structural issues, and ineffective management practices. Our study aims to scientifically measure the efficiency of health production using a multi-dimensional approach. We seek to evaluate the differences in efficiency among different regions and provide a scientific reference for improving the overall level of health in China.
Methods
Our study utilizes statistical methods to assess the health efficiency of 31 provinces in China over the period 2010 to 2020. The analysis incorporates the conventional BCC model, the super-efficient SBM model, and the Malmquist index model within the framework of DEA modeling. And using the Dagum Gini coefficient to further analyze the differences in health productivity of China.
Results
The traditional BCC model calculated China's comprehensive health production efficiency in 2020 to be 0.732. The pure technical efficiency of 13 provinces was effective, and 6 provinces showed effective comprehensive efficiency, scale efficiency, and DEA. The SBM model assessed the average health productivity value among China's provinces in 2020, revealing Guangdong as the highest (2.276) and Qinghai as the lowest (0.351). The average value of China's Malmquist Index from 2010 to 2020 was 1.002, indicating a slight overall improvement in health production efficiency. Furthermore, the score of technological change and technological efficiency change in five provinces were more than 1. Gini coefficient had obvious downward trend from 2010 to 2020, and there was a lower level in the northeastern (0.055) and eastern (0.0989) regions.
Conclusion
China's health investment has increased over the years, leading to a notable improvement in the overall health of the population. The nation's health productivity has also been on the rise, although disparities between regions remain evident, particularly between the eastern and western regions. The government should play a significant role in establishing standardized criteria for regular evaluation of health production efficiency levels. It’s suggested to utilize digital health technologies to facilitate the exchange of information among different regions in China, thereby fostering collaborative efforts to improve overall health outcomes. This study aims to boost health productivity in western regions through strategic policy and financial interventions.
Multi-Modal EEG NEO-FFI with Trained Attention Layer (MENTAL) for Mental Disorder Prediction
Authors: Greiner Garrett , Zhang Yu 
Published: July 2024

Abstract

Early detection and accurate diagnosis of mental disorders is difficult due to the complexity of the diagnostic process, resulting inconditions being left undiagnosed or misdiagnosed. Previous studies have demonstrated that features of Electroencephalogram (EEG) data, such as Power Spectral Density (PSD), are useful biomarkers for indicating the onset of various mental disorders. Existing models using EEG data are typically trained to distinguish between healthy and afflicted individuals, and they are unable to distinguish between individuals with different disorders. We propose MENTAL (Multi-modal EEG NEO-FFI with Trained Attention Layer) to predict an individual’s mental state using both EEG and Neo-Five Factor Inventory (NEO-FFI) personality data. We include an attention layer that captures the interactions between personality traits and PSD features, and emphasizes the important PSD features. MENTAL features a Recurrent Neural Network (RNN) to model the temporal nature of EEG data. We train our model with the Two Decades Brainclinics Research Archive for Insights in Neuroscience (TDBRAIN) dataset, which consists of 1274 healthy and psychiatric individuals including over 30 different diagnoses. MENTAL is able to achieve 93.3% accuracy when trained to classify between healthy individuals and those with ADHD. When trained to identify individuals with ADHD from among 33 disorder classes, MENTAL improves accuracy from 70.5% to 81.7%. MENTAL also demonstrates over 20% improvement in predictive accuracy when trained for MDD prediction. For the multi-class classification task of three classes, MENTAL improves accuracy by nearly 10%, and for five classes, by nearly 8%. MENTAL is the first multi-modal model that utilizes both EEG and NEO-FFI data for the task of mental disorder prediction. We are one of the first groups to utilize TDBRAIN for automated disorder classification. MENTAL is accessible and cost-effective, as EEG is more affordable than other neuroimaging methods such as MRI, and the NEO-FFI is a self-reported survey. Our model can lead to acceptance and support for individuals living with mental health challenges and improve quality of life in our society.
A Novel Evolutionary Algorithm-Based Approach for Optimizing the Mix Design of High-Performance Fiber-Reinforced Concrete (HPFRCC)
Authors: yeganeh Peyman farhadi , hojatkashani Ata , Nezamabadi Maryam Firoozi , Rashti Abbas Abbas Akbarpour Nikghalb , Abbasi Hassan 
Published: July 2024

Abstract

With the increasing demand for high-performance concrete, optimizing the design of high-performance alloy-armed compounds (HPFRCC) has become a major challenge. Optimizing the mix design enables the achievement of the desired stability and ductility. This study offers an innovative way to overcome this challenge using artificial intelligence (AI). Our method uses artificial neural networks (ANN) to model the relationship between the mixed component and final HPFRCC properties. Then, we explored a wide design space using advanced distribution algorithms to determine the best combination. These algorithms are inspired by nature, such as the evolutionary algorithm (EO), which replicates the scientific evolutionary process. This study significantly reduces the need for laboratory testing by employing innovative methodologies. This significant achievement significantly optimizes design time and cost. In addition, by comprehensively comparing EO performance with other similar algorithms, the excellence and innovation of the method were demonstrated in optimizing the complex design of the HPFRCC mixture, and a new multitarget optimization algorithm called FC-MOEO/AE was used to predict the HPFRCC combination. This method can be used as a design guide to guide decision-making in the pre-construction stage.
Metrology of Warpage in Silicon Wafers Using X-ray Diffraction Mapping
Authors: Gorji Nima E. 
Published: July 2024

Abstract

X-ray Diffraction (XRD) mapping is a non-destructive metrology technique that enables the reconstruction of warpage induced on a Silicon wafer through thermo-mechanical stress. Here, we mapped the wafer's warpage using a methodology based on a series of line scans in the x and y directions and at different 90-degree rotations of the same sample. These line scans collect rocking curves from the wafer's surface, recording the diffraction angle (ω) deviated from the Bragg angle due to surface misorientation. The surface warpage reflects in XRD measurements by inducing a difference between the measured diffraction angle and the reference Bragg angle (ω − ω0) and rocking curve broadening (FWHM). By collecting and integrating the rocking curves (RCs) and FWHM broadening from the whole surface and multiple rotations of the wafer, we could generate 3D maps of the surface function f(x) and the angular misorientation (warpage). The warpage exhibits a convex shape, aligning with optical profilometry measurements reported in the literature. The lab-based XRDI has the potential to be developed to map the wafer's warpage in a shorter time and in situ, as can be perfectly performed in Synchrotron radiation source.
Protective effect of oleuropein on the brain tissue in D-Galactose-induced aging in rat model
Authors: Ranjbar Elham , Foruozandeh Hossein , Nahal Ali seidkhani , Asadoola Yousef , Ahmadi Iraj 
Published: July 2024

Abstract

Background
Many researches have indicated that Oleuropein (OLE) has potential ability to decrease oxidative stress and inflammation. So, In the present investigation, we explored the protective effect of OLE on brain aging induced by d-galactose (D-Gal) in a rat model..
Methods and results
In this study, 40 Wister male adult rats were categorized into 5 groups. Group 1 received normal saline, while group 2 was administered 100 mg/kg/ip D-Gal. The rats in groups 3 to 5 were orally administered D-Gal (100 mg/kg) once a day. Additionally, these groups were simultaneously subjected to different doses of OLE (20, 40 and 80 mg/kg, respectively) through oral administration. All administrations were done once a day for 8 consecutive weeks. 24 hours after last treatment motor activity and memory impairment were evaluated. Then, the rats were sacrificed and brain samples were collected for evaluating biochemical markers (BDNF, MDA, PC, GSH, GPX, CAT , SOD, IL-1β and TNF-α) and gene expression (SIRT1 and PGC1).
The results showed that D-Gal significantly reduced motor activity and memory performance (P<0.05). It also signiﬁcantly reduced the GPx, CAT and SOD activities, GSH and BDNF levels as well as SIRT1 and PGC1 expression, and, significantly increased PC, MDA TNF-α and IL-1β levels in the brain tissue (P<0.05). Administration of OLE restored all of the above parameters close to control group.
Conclusion
The findings illustrated that OLE attenuates locomotor , cognitive dysfunction and age related neuronal dysfunction. The neuroprotection of OLE can be attributed to its potential antioxidant and anti-inflammatory properties and activation of age preventing genes.
Assessment of a constructed community of native geophytes and sedum species as a habitat analog for extensive green roofs in an urban East Mediterranean environment
Authors: Fabian Monika , Talhouk Salma N. 
Published: July 2024

Abstract

Extensive green roof research has primarily focused on cooler, wetter climates, resulting in a lack of knowledge of Mediterranean conditions. This long-term study addresses this gap by assessing a constructed plant community of native Mediterranean geophytes and Sedum species. While both are individually recognized for their resilience to prolonged dry periods, their combined performance has been underreported. We studied the performance of 15 Mediterranean geophytes combined with one native sedum on an unirrigated extensive green roof for four years. Data collection included plant survival, number of plants, spread, flowering, and new species recruitment. Throughout the study, eight geophytes did not survive, five increased in number, one remained stable, and two declined. Five geophytes readily spread, one occupied the same space, and one decreased. Most surviving geophytes flowered. Sedum spread vegetatively and flowered consistently. Seven native species were recruited. By the end of the experiment, vegetation cover was 100% (47% Sedum,44% geophytes,12% overlapping vegetation,21% new native species). The findings underscore the importance of long-term studies to observe plant dynamics and reveal the possibility of constructing new urban habitats thus contributing valuable insights for green roof development in Mediterranean cities.
Garbage Overflow Detection Algorithm Based on Improved YOLOv8n
Authors: Liu Feiyang , Zhou Ruiqi 
Published: July 2024

Abstract

Unprecedented urbanization and population growth have led to an increasing amount of domestic waste, posing significant challenges to urban environments and aesthetics worldwide. This paper proposes an improved garbage detection system based on YOLOv8n. The system uses target detection algorithms to identify garbage and trash cans in road images, determining if trash cans are overflowing and need cleaning. Firstly, a Deformable Attention Mechanism (DAT) is introduced into the backbone network, incorporating dynamic sampling points. Secondly, an auxiliary head is integrated into the model's head for training, providing deep supervision. Finally, a novel Inner-MPDIoU loss function is proposed to offer more precise evaluation results and enhance generalization ability. Comparative experiments show that the algorithm achieves a mean Average Precision (mAP) of 94.0%, significantly improving feature extraction and detection accuracy.
Heteroatom engineering enhancing thermoelectric power factor of molecular junctions
Authors: Li Yuan , Peng Wuxian , Chen Ningyue , Xie Yu , Ma Liang , Lü Jingtao 
Published: July 2024

Abstract

Engineering power factor (PF) of molecular junctions is one of the most attractive research in the field of thermoelectronics for the applications in thermal management and high-performance thermoelectric energy conversion at the nanoscale. Here, we modified the chemical structure of self-assembled monolayers (SAMs) formed by the widely investigated alkanethiolate (Cn-SH, n = 5, 8, 11, 14) through heteroatom substitutions, including the terminal iodine (I) atom substitution and replacing backbone methylene units (-CH2-) with oxygen (O) atoms, to obtain iodo-substituted oligo(ethylene glycol) thiolates (I-(C2O)m-C2-SH, m = 1, 2, 3, 4). We carried out the electrical tunneling and thermoelectric measurements based on the eutectic Ga-In technique (EGaIn) and found that the electrical conductance (G) and Seebeck coefficient (S) of the SAMs with I-(C2O)m-C2-SH can be enhanced simultaneously compared to the length-matched SAMs of Cn-SH (n = 3m + 2), resulting in the PF of I-(C2O)4-C2-SH being over 5 orders of magnitude higher than that of C14-SH, which was attributed to the resonant states contributed from the substituted I-(C2O)m-C2-SH near the Fermi energy. This study underscored the significance of chemically engineering the organic molecules to dramatically boost PF of molecular junctions for the further applications of high-efficient nanoscale thermoelectric devices.
The Application of i-Tasser and related studies to predict the full-length structure, thermodynamic states and functional analysis of the Kirsten Rat Sarcoma Virus (KRAS) protein; An observation of KRAS structural and functional integrity.
Authors: KADIR SDANISH , CHOWDHURY TANVIR , Saha Mrinal Kranti 
Published: July 2024

Abstract

KRAS (Kirsten Rat Sarcoma Virus) is a Ras (Rat Sarcoma virus) family homologous. Due to its structural characteristics and biochemical properties, it’s been regarded as one of the most common drivers in various cellular signaling pathways. Due to its biochemical and pharmacological importance, KRAS been regarded as the “Holy Grail” of drug discovery. To understand the structure and thermodynamics of this protein, we tried to focus on the confirmational and functional portion of this specific protein. “i-Tesser” is applied to predict the structure of KRAS. A prediction for the secondary and full-length 3D structure been developed. Additional generation of the B factor value, Solvent accessibility, ligand bonded structure, as well as the 5 different thermodynamic state models of the KRAS and their functions are analyzed. The primary, metastable, ligand-bounded reactive states are visualized with the additional application of NAMD (Nanoscale Molecular Dynamics) and VMD (Visualization Molecular Dynamics). The drawn models showcase a C score value ranging between (-0.02 to -1.45) and Cluster density (0.0683 to 0.2835), along with a standard deviation value of (0.704983). Predicted secondary, 3D, and Thermodynamic models are drawn and supported by modeling their Solvent accessibility and B factor values. The 5 different models and the related structural and functional analysis provide additional information about the stability of KRAS structure and its function.
Knowledge Awareness of Syrian Private University students about Anticogulin (types, mechanism of action, indications, and side effects)
Authors: Aji Ammar , Affouf Rula , Chamieh Marwan 
Published: July 2024

Abstract

Objective: This study aims to know the awareness of students at the Syrian Private University about thinners (their types, mechanism of action, indications, and side effects).
Methods and materials: A cross-sectional study in which 267 students from the Syrian Private University participated. Data were collected through a Google Form in the period between 1/6/2024 and 7/6/2024. Voluntary participation in the study is considered an informed consent. The data was analyzed by SPSS program.
Results: The sample size was 267 participants from various colleges, most of whom were from the College of Human Medicine (53.9%), the average age was 23.21 years, and the majority of students were in the sixth, fifth, and third years (35.2%, 23.6%, and 12.7%, respectively). Students who know clopidogrel 62.9%, those who know prasugrel 31.5%, those who know Ticagrelor 39%, those who know warfarin 76%, those who know dabigatran 34.5%, those who know apixaban 47.2%, those who know aspirin 91%, those who know rivoroxaban 50.9%, and those who know Edoxaban 40.4%, and those who know heparin 30.3%.
Conclusion: Health educators should place special emphasis on students who have predicted poor knowledge and poor disposition toward dispensing diluted medications without an actual indication.
Management Of Spleen Trauma In Damascus Hospital
Authors: Albaghajati Sara , Sara Samer 
Published: July 2024

Abstract

Objective: Our study aims to study blunt and penetrating traumatic splenic injuries, their management methods (Surgical or conservative) and complications.
Methods: A retrospective cohort study was conducted in the Department of Surgery at Damascus Hospital between 2015 and 2023. The study included all patients who suffered from penetrating and blunt traumatic splenic injury and were admitted to the surgery department. Data and information were tabulated using Excel spreadsheet program and then data were analyzed using SPSS-25. The results were compared with international studies according to mortality and morbidity rates perioperatively.
Results: The study included 98 patients (mean age 19.03 years with standard deviation 17.46 years, male and female ratio 71.4% and 28.6% respectively), 99% of blunt injuries, 1% of penetrating injuries, most of the injuries were grade IV (45.6% of 22 patients), most of the injuries were isolated (92.9%), 86% of stable patients (n=86) were treated surgically (91.9% excisional surgery, 8.1% conservative surgery), and 14% of them were treated conservatively, most of the unstable patients were treated surgically (91.7% excisional treatment, 8.3% conservative surgery), mortality rate 11.2% of all patients.
conclusion: Allocating a section in the emergency intensive care unit to follow up on patients with abdominal trauma, which is supervised and followed up by a specialized team that ensures close monitoring of the patient in the required manner, with the possibility of conducting radiological and laboratory investigations within this section at the required speed and at any time.
Modulating the value of positive feedback does not influence expectation change in major depression – What can be learned from a failed replication?
Authors: Houben Mimi , Rief Winfried , Gärtner Thomas , Kube Tobias 
Published: July 2024

Abstract

Background: Depression is related to a reduced update of negative expectations in response to positive information. Here, we aimed to replicate that cognitive immunization (a cognitive devaluation of expectation-disconfirming information) modulates expectation updating in depression. Further, we examined how other cognitive factors (i.e., memory, interpretation) relate to cognitive immunization.
Method: We examined 139 inpatients (18-75 years) diagnosed with major depression. Participants completed a false-feedback task, in which they received unexpectedly positive standardized feedback. Cognitive immunization was manipulated via text that framed the feedback as particularly valid vs. invalid, relative to a distraction-control group and a no-instruction control group.
Results: There were no significant group differences in expectation updating. One interpretation questions the effect of the manipulation of cognitive immunization, which was not successful according to the manipulation check. The experimental conditions did not differ in their memory or interpretation of the feedback. However, negative interpretations were associated with elevated cognitive immunization.
Conclusions: Our study failed to replicate that cognitive immunization modulates expectation updating in depression - most likely due to the failure of the cognitive immunization manipulation. Future research may need to use a stronger and easier to understand manipulation (e.g., video instead of text; simpler wording) to modulate cognitive immunization successfully.
Hyperspectral remote sensing image classification based on enhanced pseudo 3D features and salient band selection
Authors: Li Ningyang , Wang Zhaohui , Wang Lei 
Published: July 2024

Abstract

Hyperspectral classification is a research hotspot in the field of remote sensing. Recently, 3D convolutional neural networks (CNNs) have achieved better classification performances than traditional machine learning algorithms. However, because of the large kernel size and spectral redundancy, the classification accuracy and efficiency of existing CNN-based methods are still restrained. In this paper, a lightweight model based on the enhanced pseudo 3D features and salient band selection is proposed for HSI classification. Specifically, an enhanced pseudo 3D convolution block is constructed to extract spectral-spatial features with less parameters. Then, a salient band selection block without parameters is designed to relieve the spectral redundancy. To obtain the diverse spectral dependency, a local-connected layer is introduced to explore the interactions between adjacent bands. By integrating these blocks, deep spectral-spatial pseudo 3D features can be well prepared for classification. Experiments on three HSI data sets show that the proposed model outperforms the state-of-the-arts. Source code is available at https://github.com/ningyang-li/EP3FEN.