bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis of flow behavior as influenced by reservoir with flow regularization
Authors: Generoso Tarcila N. Neves , Silva Demetrius David da , Rodrigues Lineu Neiva , Amorim Ricardo Santos Silva , de Almeida Laura Thebit 
Published: April 2022

Abstract
Understanding the behavior of reservoirs with flow regularization formed by hydroelectric power plants is essential for assessing water availability and, consequently, for planning the use of water resources, especially in downstream positions. The operationalization of reservoirs can be influenced both by climatic characteristics and by the consequences resulting from human actions in the basin. Therefore, the objective of this study was to evaluate the existing relationships between the inflows and outflows of a reservoir, as well as with the conventional streamflow gauge stations downstream of the dam. In addition, the aim was also to evaluate trends in the behavior of minimum, average and maximum flows, in the post-operation period, considering the characteristics of rainfall and irrigation in the region. The results indicated that reservoir operationalization is strongly related to the behavior of inflows, especially when considering analyses in quarterly periods, also affecting the flow in the streamflow gauge stations downstream. Moreover, a reduction was also verified in all variables analyzed related to inflows and outflows, as well as in the stations downstream of the dam, except for the maximum flow in the station farthest from the reservoir, which showed a stationary behavior. The reductions observed in the flows may be related to the increase of almost three times in the area irrigated by center pivot in the basin; however, the same cannot be said in relation to the annual rainfall regime of the region, since it showed a stationary behavior for most stations evaluated.
The AppNL-G-F mouse model of Alzheimer’s disease is refractory to regulatory T cell treatment
Authors: YSHII Lidia , Mascali Loriana , Kouser Lubna , Lemaitre Pierre , Marino Marika , Dooley James , Burton Oliver , Haughton Jeason , Callaerts-Vegh Zsuzsanna , de Strooper Bart , Holt Matthew G , Pasciuto Emanuela , Liston Adrian 
Published: April 2022

Abstract
Background: Alzheimer’s Disease is a neurodegenerative disease with a neuroinflammatory component. Due to the multifunctional capacity of regulatory T cells to prevent and reverse inflammation, regulatory T cells have been proposed as a potential therapeutic in Alzheimer’s Disease, either as a direct cell therapy or through the use of IL2 as a biologic to expand the endogenous population. Methods: Here we characterize the longitudinal immunological changes occurring in T cells in the AppNL-G-F mouse model of Alzheimer’s disease. Results: Age-dependent immunological changes, in both the brain and periphery, occurred in parallel in both AppNL-G-F mice and control AppNL mice. As the endogenous IL2 axis was disturbed with age, we sought to determine the effect of IL2 supplementation on disease progression. Using a genetic model of IL2 provision in the periphery or in the brain, we found that expanding regulatory T cells in either location was unable to alter the progression of key pathological events or behavioral changes. Conclusions: These results suggest that either the AppNL-G-F mouse model does not recapitulate key regulatory T cell-dependent process of Alzheimer’s disease, or that regulatory T cell therapy is not a promising candidate for APP-mutation-driven Alzheimer’s disease.
Deep Learning Solution for Frequency Domain Diffuse Optic Tomography (FDDOT)
Authors: Kazanci Huseyin Ozgur , ORAL Okan 
Published: April 2022

Abstract
In this work, deep learning neural network architecture was applied to the well-known diffuse optic tomography problem. Frequency Domain Diffuse Optic Tomography (FDDOT) modality was selected as reference simulation system. Sources and detectors were placed on tissue imaging geometry. Back-reflection geometry has 8 sources and 8 detectors on tissue imaging geometry. Background phantom tissue absorption coefficient ma=0.3 cm-1, scattering coefficient ms=100 cm-1. One inclusion which its absorption coefficient ma=0.7 cm-1 was embedded in two different location in 20×20×20 grid sized tomographic cube. These two different scenarios were tested to reconstruct the inclusion image by using Matlab™ deep learning functions. Two different inclusion images were successfully reconstructed with the similar shape of original inclusion in the same 3d location. In deep learning structure, Matlab’s convolution layer, cross channel normalization layer, fully connected layer, regression layer was used. In training network options, stochastic gradient descent with momentum method with validation data was selected. In this work, instead of using classical inverse problem solution algorithms deep learning method was used.
Effects of mRNA expression of five Notch ligands on prognosis of gastric carcinoma
Authors: Li Yunlong , Xie Fengni , Zhang Huimin , Wu Xiao , Ji Gang , Li Jipeng , Hong Liu 
Published: April 2022

Abstract
Objectives Notch ligands are expression changes in a great many malignancies including gastric cancer (GC) frequently. The prognostic value of each Notch ligands in GC patients remains lack of large sample data results. In present research, we researched the prognostic value of Notch ligands in GC patients in order to fill the shortage areas. Methods We used an online database (http://kmplot.com/analysis/index.php?p= service & cancer gastric) to identify the relationship between mRNA expression of each Notch ligand and overall survival (OS) in GC. We analyze the relevance of overall survival and clinical data which includes gender, Lauren's classification, differentiation, clinical stage and treatment. Results The study found that high DLL1, DLL3, DLL4 and JAG2 mRNA expression were tied to worse OS in all GC patients followed up for 10 years. There is no significant relevance to the expression of JAG1 mRNA and OS in patients with GC. We also did a survey of each Notch ligands in different clinical and pathological features present different prognosis. Conclusion The information will help to better understand the biology of gastric cancer heterogeneity, provide more accurate prognostic evaluation tools and provide new targets for targeted drug development besides.
Perspectives of older adults, caregivers, healthcare providers on frailty screening in primary care: a systematic review and qualitative meta-synthesis
Authors: Feng Hui , Nan Jiahui , Duan Yunzhu , Wu Shuang , Liao Lulu , Li Xiaoyang , Zhao Yinan , Zhang Hongyu , Zeng Xianmei 
Published: April 2022

Abstract
Background: Screening is often recommended as a first step in the process of frailty management. Many guidelines call to implicate frailty screening into practice in the primary care setting. However, few countries or organizations implement it. Understanding and clarifying the stakeholders' views and issues faced by the implementation is essential to the successful implementation of frailty screening. However, the systematic review on stakeholders' views of frailty screening in primary care is decidedly limited. Our objective was to explore the perspective of older adults, caregivers, and healthcare providers on frailty screening and determine the enablers and barriers to implementing frailty screening in primary care. Methods: A systematic search of six databases and other resources was conducted following JBI’s three-step search strategy. The search resulted in 7362 articles, of which 97 were identified for further assessment according to the inclusion criteria. After the full-text screening, quality assessment and data extraction were carried out using the tools from Joanna Briggs Institute (JBI). Moreover, reviewers used the approach of meta-aggregative of JBI to analyze data and synthesis the findings. Results: Six studies were included. A total of 63 findings were aggregated into 12 categories and then further grouped into three synthesized findings:1) stakeholder capacity; 2) opportunity in the implementation of frailty screening; 3) motivation in the implementation of frailty screening. These themes can help identify what influences the implementation of screening from the perspective of stakeholders.Conclusions: This meta-synthesis provides evidence on the barriers and enablers of frailty screening in primary care, from the aspects of psychological, physical, social, material, etc. However, Stakeholder perspectives and perceptions of frailty screening have not been adequately studied. More research and efforts are needed to explore the influencing factors and address the existing barriers.
Machine Learning Compensation of Fiber Nonlinear Noise
Authors: Melek Marina Medhat , Yevick David 
Published: April 2022

Abstract
This paper examines artificial intelligence (AI) methods for compensating the distortion experienced in optical communication systems resulting from fiber nonlinearity. To identify the resulting degree of improvement afforded by machine learning methods, the procedures are applied to a model of a typical single frequency optical communication system with, a 3200km fiber length, double polarization, and a 16-QAM modulation format. The performance of transmitters and receivers that incorporate Neural Networks (NNs) are in particular examined for different values of the nonlinear coefficient \(\left(\gamma \right)\). Both of these are found to improve the system Q-factor for all values of\(\gamma\) although the degree of enhancement is dependent on the signal to noise ratio. The structures studied include Siamese neural networks (SNN) implemented at the receiver end and two-stage architectures that employ NNs at the transmitter together with a classifier at the receiver side. Here classifiers ranging from simple decision tree structures to boosting, forests, extra trees, and Multi-layer perceptron (MLP) were examined and found to provide significant enhancement for \(\gamma >\) \(4{W}^{-1}k{m}^{-1}\). The optimal performance for highly nonlinear systems was achieved with two-stage systems with random forest or extra tree AI methods at the receiver. Empirical equations are also presented for each AI technique that relates the Q-factor enhancement to \(\gamma\) and the computational resource requirements (the number of included triplet terms).
MISPR: An automated infrastructure for high-throughput DFT and MD simulations
Authors: Atwi Rasha , Bliss Matthew , Makeev Maxim , Rajput Nav Nidhi 
Published: April 2022

Abstract
Computational tools provide a unique opportunity to study and design optimal materials by enhancing our ability to comprehend the connections between their atomistic structure and functional properties. However, designing materials with tailored functionalities is complicated due to the necessity to integrate various computational-chemistry software (not necessarily compatible with one another), the heterogeneous nature of the generated data, and the need to explore vast chemical and parameter spaces. The latter is especially important to avoid bias in scattered data points-based models and derive statistical trends only accessible by systematic datasets. Here, we introduce a robust high-throughput multi-scale computational infrastructure coined MISPR (Materials Informatics for Structure-Property Relationships) that seamlessly integrates classical molecular dynamics (MD) simulations with density functional theory (DFT). By enabling high-performance data analytics and coupling between different methods and scales, MISPR addresses critical challenges arising from the needs of automated workflow management and data provenance recording. The major features of MISPR include automated DFT and MD simulations, error handling, derivation of molecular and ensemble properties, and creation of output databases that organize results from individual calculations to enable reproducibility and transparency. In this work, we describe fully automated DFT workflows implemented in MISPR to compute various properties such as nuclear magnetic resonance chemical shift, binding energy, bond dissociation energy, and redox potential with support for multiple methods such as electron transfer and proton-coupled electron transfer reactions. The infrastructure also enables the characterization of large-scale ensemble properties by providing MD workflows that calculate a wide range of structural and dynamical properties in liquid solutions. MISPR employs the methodologies of materials informatics to facilitate understanding and prediction of phenomenological structure-property relationships, which are crucial to designing novel optimal materials for numerous scientific applications and engineering technologies.
“Why don’t I look like her?”: How adolescent girls view social media and its connection to body image
Authors: Papageorgiou Alana , Fisher Colleen , Cross Donna 
Published: April 2022

Abstract
BackgroundAdolescent girls appear more vulnerable to experiencing mental health difficulties from social media use than boys. The presence of sexualized images online is thought to contribute, through increasing body dissatisfaction among adolescent girls. Sexual objectification through images may reinforce to adolescent girls that their value is based on their appearance. This study explored how sexualized images typically found on social media might influence adolescent girls’ mental health, in positive and/or negative ways.MethodsIn-depth interviews were conducted with girls aged 14-17 years (n=24) in Perth, Western Australia. Data were analyzed using thematic analysis.ResultsParticipants identified body image as a major concern, reporting negative appearance comparisons when viewing images on social media. Appearance comparisons were perceived to exacerbate adolescent girls’ appearance-based concerns. Comparisons also influenced adolescent girls’ efforts to change their appearance and seek validation on social media. The importance of awareness and education from a younger age about social media and its influence on body image was emphasized, as was the need for strategies to promote positive body image and counteract negative body image. ConclusionThe findings of this study have important implications for professionals working with adolescent girls and for the development of health promotion programs addressing social media use and body image concerns.
A Novel Method for Predicting Ideal Postoperative Upper Instrumented Vertebra Tilt to Prevent Lateral Shoulder Imbalance after Scoliosis Correction Surgery
Authors: Zhang Wen , Jiang Zhensong , Zhang Weimin , Li Tao , Sun Jianmin , Cui Xingang 
Published: April 2022

Abstract
Background: Lateral shoulder imbalance (LSI) is reflected radiologically by the clavicle angle (CA). How to achieve postoperative lateral shoulder balance (LSB) after scoliosis correction surgery remains unclear.Methods: In the current study, by using the preoperative upper instrumented vertebra (UIV) tilt, CA, the flexibility between T1 and the UIV, the ideal postoperative UIV tilt was predicted based on the following formula: ideal postoperative UIV tilt = preoperative UIV tilt – the flexibility between T1 and UIV – preoperative CA. The reliability of the formula was verified through a retrospective analysis, and 76 scoliosis patients were enrolled and divided into three groups based on the postoperative shoulder balance: 1) the whole group (n = 76); 2) the LSI group (n = 26); and 3) the LSB group (n = 50). The pre- and postoperative CA, UIV tilt, T1 tilt, flexibility between T1 and the UIV, and ideal UIV tilt were measured or calculated using the formula mentioned above. The feasibility of this method in achieving LSB by establishing the predicted ideal UIV tilt intraoperatively using the improved crossbar technique was verified through a prospective analysis, and 13 scoliosis patients were enrolled. Results: In the retrospective study, there was a significant correlation between the difference in the actual and ideal postoperative UIV tilt values and the postoperative CA, with correlation coefficients in the whole, LSI and LSB groups of 0.981, 0.982 and 0.953, respectively (p < 0.001). In the prospective study, all patients achieved satisfactory LSB, with a correlation coefficient between the difference in the actual and ideal postoperative UIV tilt values and the postoperative CA of 0.939 (p < 0.001).Conclusions: Using the formula preoperatively to predict an ideal postoperative UIV tilt and controlling the intraoperative UIV tilt with the improved crossbar technique may be an effective digital method for achieving postoperative LSB and has important clinical significance.
Pattern and rate in the Plio-Pleistocene evolution of modern human brain size
Authors: Gingerich Philip D. 
Published: April 2022

Abstract
Fourteen studies of brain size evolution in Plio-Pleistocene hominins published over the past fifty years show substantial long-term increase in endocranial volume (ECV) for the broad lineage leading to modern humans. The median generation-to-generation step rate for a consensus time series of ECV values, h0 = 0.15 standard deviations per generation, is almost identical to the median step rate observed in modern biological field studies. When specimens are aggregated in a series of 100 k.y. time bins to reflect the precision of their geological ages, temporal scaling identifies four successive phases of stasis and change that are significantly different from random. Phase I from about 3.2 to 2.0 million years before present is an initial phase of relative stasis. Phase II from 2.0 to 1.5 m.y. is a phase of directional brain size increase. Phase III from 1.5 to 0.7 m.y. is a second phase of stasis. Finally, Phase IV from about 0.7 m.y. to 10 k.y. is a second phase of directional increase. The tempo (rate) and the mode (stasis, random, or directional change) of an evolutionary time series are related to each other, and both are related to the time scale chosen for analysis.
Applying Intelligent Reflective Surface to Channel Phase Probing in Wireless Secret Key Generation
Authors: Lu Xinjin , Lei Jing , Shi Yuxin , Li Wei 
Published: April 2022

Abstract
Aiming at the problem of secret key generation in the static wireless communication environment, this paper proposes a scheme applying intelligent reflective surface to channel phase probing (IRS-CPP) in wireless secret key generation. Firstly, both legitimate parties utilize OFDM signals for channel probing to obtain the corresponding channel phase response. Secondly, the passive elements in the IRS are used to reflect the probing signal, which can effectively change the signal phases. Finally, the secret key can be obtained after reconciliation and privacy amplification. This scheme makes full use of the reciprocity of the phase response in wireless channels, and applys the IRS elements to change the static environment indirectly. Compared with the existing key generation scheme, the proposed scheme effectively improves the performance of secret key generation in static environments.
Development of EST-SSR markers and population genetic structure and genetic diversity of the Malus transitoria (Batalin) C. K. Schneider in Qinghai-Tibetan Plateau
Authors: Guo Xudong , Zhang Defang , Bai Linna 
Published: April 2022

Abstract
Malus transitoria (Batalin) C. K. Schneider is a shrub or small trees species native to in and around the Qinghai Tibet Plateau (QTP). We analyzed 142 samples from 8 natural populations of M. transitoria collected from the QTP using 18 pairs of EST-SSR markers. Genetic diversity was high at the species level showed the mean expected heterozygosity (HE) and Shannon’s information index (I) per population were 0.573 and 0.921, and the genetic diversity of the WD population (HE=0.595, I=0.974) was the highest, whereas that of the BS population (HE=0.541, I=0.870) was the lowest. The mean Gene Flow (Nm) was 6.076, and the genetic diversity of the MKH population (Nm = 5.034) was the lowest. Molecular variance analysis (AMOVA) showed moderate genetic differentiation among populations, that Within Populations variation (95%) was significantly higher than Among Populations variation (5%), which was consistent with the genetic differentiation coefficient (Fst = 0.057). STRUCTURE analysis showed 2 clusters grouped similar to the Unweighted Pair Group Method with Arithmetic (UPGMA) clustering and principal coordinates analysis (PCoA). We speculate that due to long-term orogeny, gene exchange between populations is blocked, resulting in small gene flow and loss of genetic resources. This research investigated the genetic diversity and structure of natural populations of M. transitoria to provide a scientific basis for the conservation, breeding, and rational utilization of this tree species germplasm resources in QTP.
Prevalence and correlates of depression and anxiety in patients with functional anorectal pain
Authors: Dong Liping , Sun Ting , Tong Ping , Zhang Jinglang , Guo Jia 
Published: April 2022

Abstract
Introduction: Patients with functional anorectal pain (FAP) often have psychological distress, impaired quality of life, increased health care utilization, and even suicidal tendencies. However, there are limited data on the psychological correlates in Chinese patients with FAP. Therefore, this study aimed to examine the prevalence of depression and anxiety and the related psychosocial factors among Chinese patients with FAP.Methods: We used a cross-sectional research design to recruit 100 patients with FAP in SuBei Hospital’s multidisciplinary clinic for pelvic floor disorders between January and December 2021. Information on demographic and disease characteristics was collected. Depressive and anxiety symptoms were assessed using the Patient Health Questionnaire Depression (PHQ-9) and Generalized Anxiety Disorder Questionnaire (GAD-7). Multiple logistic regression analysis examined factors associated with depression and anxiety.Results: The prevalence of depressive and anxiety symptoms among patients with FAP were 55 % and 46 %, respectively. Being a woman, specific marital status(single, divorced, separated,etc), longer duration of FAP, and sleep disturbance were significantly associated with an increased risk of depressive symptoms. Additionally, specific marital status(single, divorced, separated, etc), sleep disturbance, high Visual Analogue Scale score are associated with anxiety symptoms.Conclusions: Depressive and anxiety symptoms are prevalent in patients with FAP. Several sociodemographic and clinical predictors are identified. There is a need for psychologists to be involved in the treatment of patients with FAP. Multidisciplinary treatment may be the best strategy.