bluuebunny/crossref_metadata_2025_split huggingface dataset:
Putative Juvenile Terrorists: The Relationship between Multiple Traumatization, Mental Health, and Expectations for Reintegration among Islamic State Recruited Adolescent and Young Adult Fighters
Authors: Mohammed Rezhna , Neuner Frank 
Published: June 2022

Abstract
Background: in several conflicts worldwide children are recruited as fighters in irregular forces. These children need to be reintegrated into the society after the conflict. However, concurrent to various reservations in the communities, the reintegration of former child soldiers is challenged by the fact that many of the affected children were indoctrinated by the armed group and traumatized through war events. Even several years after the defeat of the terrorist organization ISIS in Iraq, systematic efforts towards the reintegration of children who had been recruited by ISIS are notably absent. Methods: we conducted clinical interviews with a sample of N = 59 adolescents and young adults who were incarcerated for terrorism in the prisons of the Kurdistan Region of Iraq (KRI) to assess levels and types of trauma exposure, PTSD, depression, readiness to reintegrate and ongoing identification with ISIS. Results: we found high levels of PTSD and depression that were associated with trauma exposure. The subjective readiness to reintegrate into the communities was associated with trauma exposure and was mediated by depression, even after controlling for the influence of ongoing identification with armed group. Conclusion: the study indicates that trauma-related mental ill-health should be considered in efforts to reintegrate young former terrorists.
The Genetic Architecture of Morphological Scaling
Authors: Shingleton Alexander , Wilcox Austin , Vea Isabelle , Frankino Antony 
Published: June 2022

Abstract
Morphological scaling relationships between the sizes of individual traits and the body captures the characteristic shape of a species, and the evolution of scaling is the primary mechanism of morphological diversification. However, we have almost no knowledge of the genetic architecture of scaling, critical if we are to understand how scaling evolves. Here we explore the genetic architecture of population-level morphological scaling relationships – the scaling relationship fit to multiple genetically-distinct individuals in a population – by describing the distribution of individual scaling relationships – genotype-specific scaling relationships that are unseen or cryptic. These individual scaling relationships harbor the genetic variation that determines relative trait growth within individuals, and theory suggests that their distribution dictates how the population scaling relationship will respond to selection. Using variation in nutrition to generate size variation within 197 isogenic lineages of Drosophila melanogaster, we reveal extensive variation in the slopes of the wing-body and leg-body scaling relationships among individual genotypes. This genetic variation reflects variation in the nutritionally-induced size plasticity of the wing, leg and body. Surprisingly, we find that variation in the slope of individual scaling relationships primarily results from variation in nutritionally-induced plasticity of body size, not leg or wing size. These data allow us to predict how different selection regimes alter scaling in Drosophila and is the first step in identifying the genetic targets of such selection. Our approach provides a general framework for understanding the genetic architecture of scaling, an important prerequisite to explaining how selection changes scaling and morphology.
MUC16 promotes Triple-Negative Breast Cancer Lung Metastasis by Modulating RNA- Binding Protein ELAVL1/HUR
Authors: Chaudhary Sanjib , Maurya Shailendra Kumar , Nallasamy Palanisamy , Saravanakumar Marimuthu , Shah Ashu , Atri Pranita , Ramakanth Chirravuri Venkata , Lele Subodh M. , Seshacharyulu Parthasarathy , Ponnusamy Moorthy P. , Nasser Mohd W. , Batra Surinder K. , Lakshmanan Imayavaramban 
Published: June 2022

Abstract
Background: Triple-negative breast cancer (TNBC) is highly aggressive with an increased metastatic incidence compared to other breast cancer subtypes. However, due to the absence of clinically reliable biomarkers and targeted therapy in TNBC, chemotherapy still remains the standard of care. Hence, there is an urgent need to understand biological mechanisms that lead to identifying novel therapeutic targets for managing metastatic TNBC disease. Methods: Clinical significance of MUC16 and ELAVL1 were examined using breast cancer TCGA data. Microarray was performed using MUC16 knockdown and scramble breast cancer cells and identified MUC16 associated genes using RNA immunoprecipitation and metastatic cDNA array. Metastastic properties of MUC16 was evaluated in MUC16 knockdown using tail-vein metastastic experiments. Results: Here, we show that MUC16 is highly expressed in TNBC and correlates with its target gene Hu antigen R (HuR) through global transcriptomic analysis. Depletion of MUC16 showed decreased invasion (P=0.03), migration (P=0.001), and colony formation abilities (P=0.01) of human and mouse TNBC cells. MUC16 depleted cells injected mice showed less likely to develop (P=0.001) lung metastasis. Notably, MUC16 and HuR were highly expressed in the lung tropic TNBC cells and breast cancer patients lung metastases tissues. Mechanistically, we identified MYC as a HuR target gene in TNBC using RNA immunoprecipitation and metastatic cDNA array. Furthermore, MUC16 knockdown and pharmacological inhibition of HuR (MS444 & CMLD-2) in TNBC cells showed the reduction in cMYC expression, suggesting the importance of the MUC16/HuR/cMYC axis in TNBC metastasis. Conclusions: Overall, our study identified MUC16 as TNBC lung metastasis promoter that acts through HuR/cMyc axis. In future, this study will form the basis to target both MUC16 and MYC amplified aggressive tumors.
Tool Wear Recognition and Signals Labeling with Small Cross Labeled Samples in Impeller Machining
Authors: Ou Jiayu , Li Hongkun , Wang Zhaodong , Yang Chao , Peng Defeng 
Published: June 2022

Abstract
Data driven deep learning method is the main way to study the condition monitoring of mechanical equipment, in which sufficient labeled signals to train the model parameters is a typical problem. The existing methods to obtain the labeled signals mainly focus on manual marking. For the non-batch impeller processing with variable working conditions, manually marking signals is not the wisest move. To solve this problem, this manuscript puts forward a deep conditional random field neural network (CRFNN) method. This framework fully utilizes the sensitivity of the conditional probability model to adjacent data marker information, and small cross labeled samples are used to predict the labels of unknown signals. At the same time, the variational autoencoder is used to convert the one-dimensional time series signal into three-dimensional image, which solves the problem that the empty tool signals have a great impact on the tool wear condition monitoring in the process of impeller blade machining. Experimental results on a CNC machining center demonstrate the effectiveness and feasibility of the proposed method, and outperforms the existing works under industrial small labeled samples.
An analytical model to study the frequency response of ultrasonic welding transducers
Authors: Yazdian Amir , Karafi Mohammad Reza 
Published: June 2022

Abstract
This paper develops an analytical 3D model of ultrasonic welding transducers. The presented model investigates the effects of the workpiece's stiffness and material properties on transducers' frequency response and mode shape. Longitudinal and lateral vibration is taken into account in the model. In order to analyze the forced vibration of the transducer, the effect of piezoelectric and excitation electrical fields are considered. The structural damping is considered as an imaginary Young's modulus. For validation of the model, a transducer, booster, and horn with specific dimensions and physical properties is modeled in ANSYS software. Its resonant frequency is compared with the mathematical model. Then, the system is fabricated for experimental tests. The resonant frequency in the analytical model, simulation, and the experimental test is achieved, 19208 Hz, 19280 Hz, and 19203 Hz, respectively. There is a 0.02% error between the analytical model and the experimental test. The Anti-resonant frequency in the analytical model is 19265 Hz which has a 0.02% error with experiment (19270 Hz). The admittance at a resonant frequency in the analytical model is 0.01755 mS which has a 0.2% error with the experiment (0.0176 mS). The mechanical quality factor of the transducer and its vibration amplitude are calculated by the developed analytical model according to the mechanical properties of components.
Association between immunosuppressants and antibody responses to SARS-CoV-2 vaccines in patients with autoimmune liver diseases
Authors: Li Hu , Wang Yuting , Ao Ling , Ke Mingxia , Chen Zhiwei , Chen Min , Peng Mingli , Ling Ning , Hu Peng , Cai Dachuan , Zhang Dazhi , Ren Hong 
Published: June 2022

Abstract
Background and aims: Little is known regarding the antibody responses of COVID-19 vaccination in patients with autoimmune liver diseases (AILD). We aim to evaluate the antibody responses and explore the impact of immunosuppressants on SARS-CoV-2 vaccines in AILD.Methods: We conducted a prospective observational study and included participants been healthy as controls and AILD. All adverse events (AEs) were recorded. IgG antibodies against the receptor-binding domain (RBD) of spike protein (anti-RBD-IgG) and Neutralizing antibodies (NAbs) were tested after the COVID-19 vaccination. In addition, SARS-CoV-2 specific B cells were detected by flow cytometry.Results: 76 patients and 136 healthy controls (HC) were included. All AEs were mild and self-limiting, and the incidences were similar between AILD and HC groups. The seropositivity rates of anti-RBD-IgG and NAbs in AILD were 97.4% (100% in HC, p = 0.13) and 63.2% (84.6% in HC, p < 0.001), respectively. The titers of anti-RBD-IgG and NAbs were significantly lower in AILD compared with HC. After adjusting for confounders, immunosuppressive therapy was an independent risk factor for the low-level anti-RBD-IgG (adjusted odds ratio [AOR]: 4.7; 95% confidence interval [CI], 1.5-15.2; p = 0.01) and reduced probability of NAbs seropositivity (AOR, 3.0; 95% CI, 1.0-8.9; p = 0.04) in AILD patients. However, regardless of immunosuppressants, the SARS-CoV-2 specific memory B cells responses were comparable between AILD and HC groups.Conclusion: SARS-CoV-2 inactivated vaccine is safe, but its immunogenicity is compromised in patients with AILD. Moreover, immunosuppressants are significantly associated with poor antibody responses to the SARS-CoV-2 vaccine.
Grandparenting and life satisfaction among Chinese elderly migrants: Mediating role of loneliness and self-esteem
Authors: Wang Hao , Yang Man , Fang Xiaoya , Hou Yanjie , Zhang Lin , Yao Jun 
Published: June 2022

Abstract
Background: Grandparenting is a common form of childcare in China. In recent years, the impact of grandparenting on life satisfaction has been widely studied. But we know little about the psychological mechanisms that link them. In addition, few studies have paid attention to elderly migrants who face the dual challenges of aging and migration. Thus, this study aims to examine the relationship between grandparenting and life satisfaction among Chinese elderly migrants, and try to explore the mediating role of loneliness and self-esteem.Methods: All 723 participants were recruited in Nanjing, Jiangsu Province, China. Firstly, we described the demographic characteristics of the participants. Secondly, we used Spearman’s correlation analysis to examine whether there were correlations between grandparenting, loneliness, self-esteem and life satisfaction. Finally, we used the PROCESS Model 6 to complete the mediation analysis.Results: Elderly migrants had a high level of life satisfaction (26.70 ± 5.47). The proportion of grandparenting was 80.4. Grandparenting was positively associated with life satisfaction among elderly migrants (r = 0.223, p < 0.001). The total effect of grandparenting on life satisfaction was 2.965 (p < 0.001). Loneliness and self-esteem mediated the relationship between grandparenting and life satisfaction. The total indirect effect was 1.414 (95%CI: 0.849, 2.014) and the ratio to the total effect was 47.7% (1.414/2.965). The mediating effect contained three paths: Loneliness (B= 0.287; 95%CI: 0.072, 0.563; Ratio= 9.7%); Self-esteem (B= 0.957; 95%CI: 0.516, 0.1.404; Ratio= 32.3%); and Loneliness → Self-esteem (B= 0.170; 95%CI: 0.040, 0.331; Ratio= 5.7%).Conclusion: Grandparenting is a common phenomenon among Chinese elderly migrants, and it is a positive predictor of life satisfaction. Loneliness and self-esteem mediate the relationship between grandparenting and life satisfaction.
Insilico screening of phytoconstituents derived from Tinospora cordifolia (Willd.) Miers as potential α-amylase and α-glucosidase inhibitors for treatment of type2 diabetes mellitus
Authors: SINGH GURPREET 
Published: June 2022

Abstract
Because of their biological properties, phytochemicals have been an essential component of nutraceutical treatment for diabetes mellitus. To establish a new technique for controlling carbohydrate metabolism and hyperglycaemia, natural phytochemicals produced from Tinospora cordifolia were tested for their anti-inhibitory effects against α-amylase and α-glucosidase enzymes. The inhibitory activity of more than 40 compounds against α -amylase and α -glucosidase was assessed using molecular docking and virtual screening approaches in this work. It was observed that Isocolumbin, Cordifoliside B, β-sitosterol, Ecdysone, Palmitoside E, Colmbin and cordiofoliside C showed a strong binding affinity for both the enzymes as compared to the clinically used metformin and Acarbose. Further these biologically active compounds are predicted to be non-toxic and noncarcinogenic. The compounds' efficacy as prospective therapeutic candidates can be due to their great affinity for the enzymes' catalytic region, which can cause a conformation change and results a reduction in enzyme activity. The findings of this study might possibly indicate to a way for creating a new class of drugs.
Study on Multispecies Solute Transport through Heterogeneous Porous Media
Authors: Gupta Kumar Rishabh , Sharma Pramod Kumar 
Published: June 2022

Abstract
The present study focuses on multispecies transport through heterogeneous porous media. An increasing exponential time-dependent dispersion is used to describe the heterogeneity of porous media. A numerical approach to the decomposition method for the study of multispecies solute transport through heterogeneous porous media has been proposed. Governing equations of multispecies solute transport have been solved numerically using the implicit finite difference technique. The effect of time-dependent dispersion has been analyzed using the exponential time-dependent dispersivity function and the same has been validated with the analytical solution. The study illustrates the solute movement involving sequential first-order decay reactions and the analysis has been carried out in three species nitrification chain and migration of radionuclides as four species. The model is used to simulate the breakthrough curves and the analysis has been done using different decay rate constants. Also, this study has been carried out on the behavior of solute concentration using an increasing macro-dispersivity function which accounts for the spatial heterogeneity of porous media. Further, spatial moment analysis has been performed on the concentration of all species and a comparison has been drawn using constant and exponential time-dependent dispersivity functions using various breakthrough curves. This analysis revealed that the mean travel distance and variance are sensitive to the change in the dispersivity function and its transformed species may not have the same transport pattern.
Geospatial temporal assessment and monitoring of land area carbon: Evidence from Adekunle Ajasin University, Akungba Akoko, Ondo State, Nigeria
Authors: AJAYI Ezekiel , BAMIDELE Bolanle Lizzy 
Published: June 2022

Abstract
This study was conducted to monitor some area carbon in Adekunle Ajasin University Akungba (AAUA) Campus to encourage tree planting alongside her edifice and discourage high rate of deforestation. This study relies solely on the use of remote sensing data to estimate carbon sequestration between year 2014 and 2020. The objective of this study is to estimate the carbon sequestration capacity in the study area using remote sensing (RS) and geographical information system (GIS) with a view to enkindling the importance of trees or forest within the University campus. Consequently, Landsat 8 TM Satellite images of year 2014 and 2020 of the study area were obtained from United States Geological Survey (USGS). The spectral vegetation index (normalised difference vegetation index) was estimate using spectral bands 4 and 5. Ten areas were chosen for this study and their coordinates obtained using GPS receiver when visited. These areas were not developed in 2014 and not fully developed as at year 2020. Through normalised difference vegetation index (NDVI) spread using Water scaler, Evapotranspiration, Potential evapotranspiration (PET), Absorbed photosynthetic active radiation (APAR) and Fraction of absorbed photosynthetic active radiation (FAPAR). The biomass carbon values were generated and the mean biomass carbon values were obtained. It was observed that 2014 had a mean biomass of 7.83 kg/m3 while the figure was 2.47 kg/m3 for 2020. The biomass carbon values per hectare were obtained as 87.00 kg/m3/ ha and 27.40 kg/m3/ ha for 2014 and 2020, respectively. Total biomass carbon of 69, 951.62 kg/m3 and 22, 031.93 kg/m3 were sequestered in 2014 and 2020, respectively for the entire study area. Results of biomass carbon for the designated locations and year using t-test were significantly different at P > 0.05. Therefore, carbon sequestration in the year 2014 was higher and better than those obtained in the year 2020 and this reduction could be attributed to forest degradation or loss of vegetation in the study locations. For environmental and carbon friendly atmosphere, green plants are encouraged to be included within urban development plan in the university campuses.
Transcritical bifurcation and flip bifurcation of a new discrete ratio-dependent predator-prey system
Authors: Li Xianyi , Liu Yuqing 
Published: June 2022

Abstract
After a discrete two-species predator-prey system with ratio-dependent functional response is topologically and equivalently reduced, some new dynamical properties for the new discrete system are formulated. The one is for the existence and local stability for all equilibria of this new system. Although the corresponding results for the equilibrium E3 have been presented in a known literature, our results are more complete. The other is, what’s more important and difficult, to derive some sufficient conditions for the transcritical bifurcation and period-doubling bifurcation of this system at the equilibria E1, E2 and E3 to occur, which are completely new. Numerical simulations are performed to not only illustrate the theoretical results obtained but also find new dynamics – chaos occuring. Our results sufficiently display that this system is very sensitive to its parameters. Namely, the perturbations of different parameters in this system will produce different bifurcations.MR(2000) Subject Classification: 39A28, 39A30.
Optimization of Thin-Film Carbon Nitride (C2N) based solar cell via Zn1−xMgxO as a buffer layer
Authors: Ahmad Waqas , Farooq Waqas , Khan Adnan Daud , Alanazi Abdulaziz , Adnan Kashif 
Published: June 2022

Abstract
Carbon nitride (C2N) based solar cell is getting cynosure in the photovoltaic research community due to their tremendous advantages over other thin-film solar cells such as environmentally friendly material nature and low fabrication cost. In this paper, we theoretically analyzed Zinc Magnesium oxide (Zn1 − xMgxO) as a buffer layer coupled with C2N as an absorber layer to form a p-n junction by using SCAPS- 1D simulation tool. ZMO as an electron transport layer (ETL) utilized with four Mg (x) doped with the concentrations of x = 0.0625, 0.125, 0.1875, and 0.25. After optimizing different layers for the proposed structure, it has been noticed that increasing the thickness of the C2N layer results in the enhancement of efficiency rate. Further, it was observed that the doping density of C2N beyond 1015 cm− 3 degrade the performance of the cell. In addition to this, the optimization of the buffer layer is performed and the optimum performance parameters were achieved at 30 nm. The theoretically modelled structure shows a great enhancement in Open circuit voltage (Voc), Short circuit density (Jsc), Fill factor (FF), and Power conversion efficiency (PCE) with regards to the presented approach. The structure is compared with different kind of other solar cells and obtained parameters shows the higher values of Voc of 1.225 V, Jsc of 18.2572 mA/cm2, FF of 84.96%, and PCE of 19.01%. The recorded results are in good agreement with the standard theoretical studies.
Existence Results of a Singular Non-linear Fractional Differential Equations Class with Nonlocal Double Integral Boundary Conditions
Authors: Yan Debao 
Published: June 2022

Abstract
This article presents the existence outcomes concerning a family of singular nonlinear differential equations containing Caputo’s fractional derivatives with nonlocal double integral boundary conditions. According to the nature of Caputo’s fractional calculus, the problem is converted into an equivalent integral equation, while two standard fixed theorems are employed to prove its uniqueness and existence results. An example is presented at the end of this paper to illustrate our obtained results.