bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improving the performance of DSSCs by modulating the electron donor and electron acceptor of dye molecules with the DTPBT group as π-bridge
Authors: Zhao Shihan , Liu Qian , Cao Jiameng 
Published: July 2022

Abstract
When the search for abundant and economically viable green energy sources is a pressing task of our time, the study of dye-sensitized solar cells (DSSCs) as a photovoltaic conversion device is particularly important. Thus, herein, to improve the performance of dye molecules with large planar dithienopyrrolobenzothiadiazole (DTPBT) as a π-bridge, the electron donor (D) and electron acceptor (A) of H1 molecule were replaced with phenanthroimidazole and rhodanine 3-acetic acid, respectively, resulting in the new molecules Q1 and Q2. The photovoltaic properties of these three molecules were investigated comprehensively, the effects of D and A changes on each performance parameter of the dye molecules were explored, and the photoelectric conversion efficiency (PCE) of DSSCs based on these dye molecules was predicted using a rational model. The results show that the selected positions of these dye molecules have similar planar distortions and that these distortions can inhibit the aggregation of dye molecules on the semiconductor surface. In addition, rhodanine 3-acetic acid as the A of the Q2 increased the light-trapping ability of the dye molecule because of the apparent red-shift of the absorption spectrum and the increase in the intensity of the photoresponse. The excited-state charge transfer data indicate that the Q2 has a unidirectional charge transfer excitation characteristic, which is favorable for generating effective photocurrents. Also, base on the suitable theoretical model, we predict a PCE of 6.15% for DSSCs based on the Q2, which is 1.3 times higher than the 4.73% for the H1. Therefore, for using large DTPBT groups as π-bridges of dye molecules, the use of suitable A will be more favorable for electron transfer and overall performance improvement, and the potential of the group can be more easily demonstrated.
Numerical simulation on flow and heat transfer in twin roll strip casting and rolling molten pool with side dams vibrating
Authors: Guo Chunyu , Xue Yuan , Yan Fusheng , Hu Xianzhong 
Published: July 2022

Abstract
A three-dimensional numerical model was established to predict the liquid level, the temperature field, the flow field, the turbulent kinetic energy, the outlet temperature and the liquid fraction in the twin roll strip casting and rolling molten pool with side dams vibrating. The numerical simulations were also conducted to compare the flow and heat transfer characteristics under different vibration frequencies and different casting temperatures. The results showed that the heat transfer was enhanced, the mixing of solutes is optimized, the strip outlet temperatures were homogenized, the kiss lines were higher, and the rolling intervals were extended as the frequency increased. Also, excessive casting temperature would cause some unexpected problems such as liquid steel leakage and unformed strips, and also make the height of kiss line uneven. Lower casting temperature would also make the strip outlet temperature more uniform and make the kiss lines higher. Through these analyses, a new approach to advancing the development of twin roll strip casting and rolling is proposed.
Prediction of Spontaneous Basal Ganglia Hematoma Expansion; Clinical Data Versus Radiology Signs Versus Radiomics; A Pilot Study
Authors: Rezaei Ali , Godwin Ryan , Prattipati Veeranjaneyulu , Tanwar Manoj , Singhal Aparna , Sotoudeh Mahsan , Sotoudeh Houman 
Published: July 2022

Abstract
Prediction the hematoma expansion (HE) of spontaneous basal ganglia hematoma (SBH) from the first non-contrast CT can improve the patient outcome. This study has been design to compare the performance of “Radiomics analysis”, “radiology signs”, and “clinical-aboratory data” for this task. We collected clinical, demographic, and laboratory from medical records in patients with SBH. CT images reviewed for the presence of radiologic signs, including Black hole, Blend, Swirl, Satellite, and Island signs, which may predict the hematoma expansion. Radiomic features from the SBH on the first brain CT were extracted, and the most predictive features were selected. Different machine learning models were developed based on clinical, laboratory, and radiology signs and selected Radiomic features to predict HE. The dataset used for this analysis included 116 patients with SBH. Among different models and different thresholds to define hematoma expansion (10%, 20%, 25%, 33%, 40%, and 50% volume enlargement thresholds), the Random Forest based on ten selected Radiomic features achieved the best performance (for 25% hematoma enlargement) with AUC of 0.9 on the training dataset and 0.89 on the test dataset. The models based on clinical-laboratory, and radiology signs had deficient performance (AUCs about 0.5–0.6). Base on our findings, Radiomic models outperform the radiology signs, clinical, laboratory, and demographic features to predict the HE. A twenty-five percent increase in the hematoma volume is likely the best threshold to predict HE by machine learning and Radiomics. The rondom forest models are probably the best models for this task.
Low-frequency Sea level changes in the Caspian Sea: long-term and seasonal trends
Authors: Azizpour Jafar , Ghaffari Peygham 
Published: July 2022

Abstract
The analysis of seasonal and long-term changes of the Caspian Sea level examined from historical long time tide gauge data in order to consider the influence of climate factors on sea-level changes in this lake system. The major peak at spectra corresponds to the annual cycle and semiannual oscillations peak is located at next vigorous. Effects of diverse global and regional factors on lake level changes are investigated by signal processing methods. Results show that annual cycle of Siberian High and Volga River discharge have the considerable effects on the Caspian Sea level changes in global and regional scales, respectively. Analyzing of seasonal cycle is revealed that Volga river discharge was significant on sea level fluctuations by one-month lag in northern and central basins and two months delay for southern basin. The long-term cycle results show ascending trend of evaporation in central basin that it is the main factor to decreasing in the Caspian Sea level since 1990s.
Impact of Digital Health Technology on Error Margins of Health Insurance Claims in Ghana: a quasi-experimental study
Authors: Adzakpah Godwin , Dwomoh Duah 
Published: July 2022

Abstract
Introduction
An efficient medical claims billing system is critical to mitigating the challenges associated with claim denials and ensuring the sustainability of providing healthcare services. This study assesses the impact of Digital Health Technology (DHT) in reducing the rate of error margins of health insurance claims submitted by health facilities to the National Health Insurance Authority in Ghana.
Methods
The study used longitudinal data on monthly claims adjustments due to errors from both paper-based and claims submitted using different DHT systems from 2010 to 2019. The rate of error margins was estimated for each month. Prais-Winsten Segmented Interrupted Time-Series analysis was used to estimate the impact of DHT systems by comparing claims data before and after the system implementation for each facility. We employed meta-analysis techniques to generate a pooled impact estimate of DHT systems on error margins of health insurance claims.
Results
The total cost of deductions due to errors from the DHT system was significantly lower than the paper-based system (DHT = 8.15%, paper-based system = 10.13%). DHT contributed to an immediate 1.31 percentage point reduction in the error margins of health insurance claims compared to the paper-based system.
Conclusion
The DHT recorded lower denied claims costs than the paper-based claims system. Scaling up the use of DHT for claims submission will reduce the rate of claim denials and ensure the sustainability of providing healthcare services.
In-vivo oogenesis of oogonial and mesenchymal stem cells seeded in transplanted ovarian extracellular matrix
Authors: Mirzaeian Leila , Eivazkhani Farideh , Saber Maryam , Moini Ashraf , Esfandiari Fereshteh , Valojerdi Mojtaba Rezazadeh , Fathi Rouhollah 
Published: July 2022

Abstract
Objective (s):
One way to overcome the recurrence of cancer cells following ovarian tissue transplantation is to use decellularized tissues as a scaffold that does not have any cellular components. These cell-free scaffolds can be seeded with different type of stem cells for ovarian restoration.
Materials and Methods
OSCs, PMSCs and BMSCs (oogonial, peritoneal and bone marrow mesenchymal stem cells, respectively) were seeded into human decellularized ovarian tissue as 4 groups: Scaffold + OSCs (SO), Scaffold + OSC + PMSCs (SOP), Scaffold + OSC + BMSCs (SOB) and Scaffold + OSC + PMSCs + BMSCs (SOPB). The produced grafts were transplanted into the sub-peritoneal space of ovariectomized NMRI mice as artificial ovary (AO). The expression of Vegf, CD34, Gdf9, Zp3, Ddx4, Amh and Lhr genes in AOs were measured by qRT-PCR. Also, histotechniques were considered to detect the anti GFP, PCNA, VEGF, GDF9, ZP3 and AMH proteins.
Results
H & E staining showed follicle-like structures in all groups; the number of these structures, in the SOP and SOB groups, were the highest. In SO group, differentiation ability to oocyte and granulosa cells was observed. Endothelial, oocyte, germ, and granulosa cell-like cells were specially seen in SOP and angiogenesis capability was more in SOB group. However, angiogenesis ability and differentiation to theca cell-like cells were more often in SOPB group. While none of the groups showed a significant difference in AMH level, estradiol levels were significantly higher in SOPB group.
Conclusion
Integration of OSCs + PMSCs and those OSCs + BMSCs were more conducive to oogenesis.
Hydrology, nitrate and sediment fluxes towards the Mediterranean Sea: case of the main North Africa catchments
Authors: ZETTAM Amin , SAUVAGE Sabine , TALEB Amina , Nouria BELAIDI , SANCHEZ-PEREZ José Miguel 
Published: July 2022

Abstract
The objective of this study is to propose a modelling approach to quantify the contribution of mains coastal catchments of North Africa in sediment and nitrate fluxes to the Mediterranean Sea. We use the Soil and Water Assessment Tool (SWAT) on the biggest coastal rivers, Moulouya (55 860 km2), Tafna (7200 km2), Chelif (44 694 km2) Oued el Kebir (8 824 km2) and Medjerda (23 213 km2). Simulation was performed monthly from 2003 to 2013. The model represents correctly the dynamics of water, sediment and nitrate flux. Rivers carry between 22 .103 to 390 103t yr-1 of sediments and Oued el Kebir contributes with 55% of the total amount, while nitrate fluxes vary from 182 to 1715 t yr-1 and Moulouya contributes with 32% of the total quantity. The simulations show us that the North African dams stocked a large amount of sediment (98%) and nitrates (39%) transported by rivers.
Spatial Distribution of Primary Radiation Damage in Microstructures
Authors: Burr Patrick , Brand Matthew , Obbard Edward 
Published: July 2022

Abstract
The universally-used theory of Norgett, Robinson and Torrens (NRT) for calculating primary radiation damage in materials assumes that materials are homogeneous. For many engineering materials, which have rich microstructures, this assumption is poor. As there are no alternative radiation damage theories that include heterogeneity, the role of the microstructure on primary radiation damage has been neglected. Here we extend the NRT formalism to account for microstructural variations and account for the damage caused in a phase by primary knock-on atoms that are produced in another nearby phase. The new approach converges to conventional NRT at suitably large length-scales, and agrees with binary collision approximation simulations for individual phases of a microstructure.
Applying the method to a ferritic superalloy, we show that the damage can vary by up to 30% from one phase to another, and up to 7% within a single phase. Substantially greater variations are predicted for more chemically heterogeneous alloys. Our new approach provides new physical insight into the interplay between microstructure and primary radiation damage.
Association of Extended Work and Higher Physical and Emotional Work Demands with Sleep Disturbance among Night-Shift Workers
Authors: Jeon Bo Min , Kim Su Hyun 
Published: July 2022

Abstract
Background: In-depth investigation of the factors that exacerbate sleep disturbance among night-shift workers is essential to develop a successful implementation strategy to improve sleep. Although some characteristics of work associated with sleep disturbances have been investigated, there are inconsistencies in the findings. This study aimed to assess the influence of working time and work characteristics on sleep disturbance among night-shift workers.Methods: This study was a secondary data analysis of a nationally representative sample of data from the fifth Korean Working Condition Survey in 2017. A total of 1,678 wage workers aged between 15 and 59 with night shift schedules were selected and analyzed. A multiple logistic regression analysis was conducted to analyze the influences of working time characteristics, including shift type, frequency of night shift, and extended work; as well as work characteristics, including physical work demands, workload, emotional work demands, social support, and communication, on sleep disturbance among night-shift workers. Results: Of those analyzed, 7.6% of night-shift workers experienced sleep disturbances. Night-shift workers with extended work and higher physical and emotional work demands were more likely to experience sleep disturbance. Conclusion: Extended work and higher physical and emotional work demands were significant factors for sleep disturbance among night-shift workers. These findings highlight the importance of adjusting work demands and mitigating extended work to reduce sleep disturbance in night-shift workers.
IL-9 stimulates an anti-tumor immune response and facilitates immune checkpoint blockade in the CMT167 mouse model
Authors: Feng Yuqian , Yan Sheng , Lam Sze Kwan , Ko Frankie Chi Fat , Chen Caoyang , Khan Mahjabin , Ho James Chung-Man 
Published: July 2022

Abstract
There is mounting evidence that interleukin-9 (IL-9) is associated with cancer although its function in lung cancer remains elusive. This study aimed to elucidate the role of IL-9 in lung cancer and the mechanisms involved. We report the detection of interleukin-9 receptor (IL-9R) expression in CMT167 cells, but not in Lewis lung carcinoma (LLC) cells. LLC or CMT167 cells were inoculated in wildtype C57BL/6J immunocompetent mice. Tumor-bearing mice were randomized on day 3 post-inoculation (8 mice per group) to receive intraperitoneal treatment with murine recombinant IL-9 (50 ng/mouse on alternate days) ± anti-programmed cell death protein 1 (anti-PD-1, 10 mg/kg, every three days) or control until reaching humane endpoints whereby tumors were harvested. In LLC tumor-bearing mice, neither tumor growth nor intratumoral T cells were affected by IL-9 treatment. Nonetheless IL-9 decreased CMT167 tumor growth and enhanced anti-tumor T cell responses, both of which were absent in IL-9R knockdown CMT167 tumors. CD8+ T cells were identified as the key effector driving IL-9-induced tumor suppression in the CMT167 model. Increased dendritic cell population and MHC-I expression were observed in IL-9-treated CMT167 tumors. Simultaneously, PD-1 and programmed death ligand 1 (PD-L1) expression by CD8+ T cells and CMT167 cells was upregulated. The combination of IL-9 and anti-PD-1 antibody synergistically suppressed CMT167 tumor and enhanced tumor-infiltrating proportion of CD8+ T cells. Taken together, our study determined the role of IL-9 in anti-tumor immunity and proposes IL-9 as a promising adjuvant to immune checkpoint blockade in lung cancer.
Physical Firmness Increases Structural Alignment
Authors: Cecutti Lorenzo , Lee Spike W.S. 
Published: July 2022

Abstract
Raising one's jammed fist is not just a common pictorial representation of struggle against the establishment but turns out to reflect a deeper connection between sensorimotor states and beliefs. The present research investigated how physical firmness, manipulated through muscle tightening, might shape beliefs. The central hypothesis, structural alignment, was tested against two other competing predictions: content extremity and content matching. Three studies provided evidence supporting structural alignment but not content matching or extremity. Specifically, the correlation between intelligence and personality lay beliefs (Studies 1-2), and the correlation between individualizing and binding moral foundations (Study 3) increased when participants jammed their fist (Study 1) or clenched their jaw (Studies 2-3). These effects emerged in the absence of mean-level differences (which would have reflected content matching or extremity). Moreover, they did not seem attributable to response bias or tiredness. Overall, sensorimotor experiences such as physical firmness can align higher-order cognitions such as beliefs in ways that are distinct from prior demonstrations of embodied cognition effects.
Whole-cell P450 biocatalysts using engineered Escherichia coli with fine-tuned heme supply
Authors: Hu Baodong , Zhou Jingwen , Li Jianghua , Chen Jian , Du Guocheng , Lee Sang Yup , Zhao Xinrui 
Published: July 2022

Abstract
By exploiting versatile P450 enzymes, whole-cell biocatalysis can be performed to synthesize valuable compounds in Escherichia coli. However, the insufficient supply of heme limits the whole-cell P450 biocatalytic activity. Here we report a strategy of improving intracellular heme supply for enhancing the catalytic efficiencies of P450s. After comparing the effects of enhancing heme transport and biosynthesis on P450 activities, intracellular heme supply was optimized through the integrated expression of necessary synthetic genes at proper ratio and the assembly of rate-limiting enzymes using DNA-guided scaffolds. By the combined use of mutated heme-sensitive biosensor and small regulatory RNA systems, the intracellular heme level was fine-tuned. The catalytic efficiencies of three different P450s, BM3, sca-2 and CYP105D7, were enhanced through fine-tuning heme supply for the synthesis of hydroquinone, pravastatin, and 7,3',4'-trihydroxyisoflavone as examples of chemical intermediate, drug, and natural product, respectively. This strategy will be useful to produce other hemoproteins with high activities.
Trade and Economic Growth: Does the Sophistication of Traded Goods Matter?
Authors: Ekanayake P. Niluka S. P. , Madsen Jakob B. , Bharati Tushar 
Published: July 2022

Abstract
Following the seminal paper of Frankel and Romer (1999), ‘Does trade cause growth?’, the income effects of aggregate trade openness have been controversial. This research shows that the type of product that is traded has first-order effects while the overall trade intensity has second-order effects on per capita income because of (i) the hierarchical structure of learning by doing in products with different levels of sophistication of the production processes; and (ii) the fertility and education effects of trade specialization following the quantity-quality tradeoff framework of Galor and Mountford (2006). Using data on trade disaggregated by the level of technological sophistication of the production process for 223 countries over the 1962-2019 period, we find that (1) the growth effects of foreign trade differ widely across technology categories; (2) high-tech trade has permanent growth effects; and (3) a significant fraction of the income effects of trade are mediated through education and fertility.JEL Codes: F14, F43, J13, O11, O33.
YOLOv4Tiny: Bearing Angle Based Pose Estimation and Semantic Segmentation For 3D Object Detection From LiDAR Point Cloud &amp; RGB-D Data
Authors: Rajendran Ramana , B.S. Murugan 
Published: July 2022

Abstract
3D object detection is a computer vision task that is used for various applications. However, it has several drawbacks due to occlusion, noise, inefficient field of view, etc. In addition, the recent LiDAR point clouds-based 3D object detection methods lack sparsity and homogeneity which affects the detection accuracy. In this paper, we detect 3D objects based on static and dynamic states by performing preprocessing, segmentation, extraction of features, classification, and regression considering RGB-D images, and LiDAR point clouds. Firstly, the quality of the image is enhanced by performing preprocessing which consists of two levels. In the first level, noise removal is performed for both RGB-D images and LiDAR cloud points by implementing Thresholding based Adaptive Median Filtering (TAMF) algorithm. In the second level, we perform point to voxel conversion for the LiDAR point clouds and fuse both RGB-D images and 3D LiDAR point clouds for better segmentation. Secondly, object segmentation is performed using Improved Mask R-CNN algorithm which creates masked instant bounding boxes by performing semantic segmentation considering both point and local-based information. Estimating pose for the segmented objects using bearing angle-based affine transformation method to extract features efficiently. Thirdly, Feature extraction is performed from the segmented 3D objects by considering high and low-level features using Attention-based YOLO V4 Tiny network and fusing both features for reducing the feature redundancy. Finally, based on the extracted feature the objects are classified as static and dynamic, and 3D bounding boxes are generated to improve the 3D object detection accuracy. The proposed work is evaluated by KITTI dataset. MATLAB R2020a simulation tool is used to perform simulation for the proposed work. The performance of the 3D object detection is evaluated in terms of several performance metrics such as accuracy, precision, recall, F-measure, computation time, and ROC-AUC curve compared to existing methods.