bluuebunny/crossref_metadata_2025_split huggingface dataset:
High-latitude precipitation as a driver of multicentennial variability of the AMOC in a climate model of intermediate complexity
Authors: Mehling Oliver , Bellomo Katinka , Angeloni Michela , Pasquero Claudia , von Hardenberg Jost 
Published: November 2022

Abstract
Centennial-scale variability of the Atlantic Meridional Overturning Circulation (AMOC) in the absence of external forcing has been identified in several climate models, but proposed mechanisms differ considerably. Therefore, better understanding of processes governing AMOC variability at these timescales is needed. Here, we analyze numerical simulations with PlaSim–LSG, an Earth System Model Intermediate Complexity (EMIC), which exhibit strong multicentennial oscillations of AMOC strength under constant pre-industrial boundary conditions. We identify a novel mechanism in which these oscillations are driven by salinity anomalies from the Arctic Ocean, which can be attributed to changes in high-latitude precipitation. We further corroborate our findings by conducting a set of millennial-length sensitivity experiments, and we interpret the mechanism by formulating a three-box model which qualitatively reproduces regular oscillations of the AMOC. While PlaSim–LSG lacks complexity compared to state-of-the-art models, our results reveal that precipitation minus evaporation (P-E) change in the Arctic is a physically plausible driver of centennial-scale AMOC variability. We discuss how this mechanism might be most relevant in climate states warmer than the present-day, raising questions about the state-dependence of multicentennial AMOC variability.
3D head-talk: speech synthesis 3D head movement face animation
Authors: Yang Daowu , Li Ruihui , qi yang , Peng Yuyi , Huang Xibei , Zou Jing 
Published: November 2022

Abstract
Speech-driven 3D human face animation has made admirable progress. However, synthesizing 3D facial speakers with head motion is still an unsolved problem. This is because head motion, as a speech-independent appearance representation, is difficult to model by a speech-driven approach. To solve this problem, we propose 3DHead-Talk, which generates 3D face animations combined with extreme head motion. In this work, we face a key challenge to generate natural head movements that match the speech rhythm. We first form an end-to-end autoregressive model by combining a dual-tower and single-tower Transformer, with a speech encoder encoding the long-term audio environment, a facial grid encoder encoding subtle changes in the vertices of the 3D facial grid, and a single-tower decoder automatically regressing to predict a series of 3D facial animation grids. Next the predicted 3D facial animation sequence is edited by a motion field generator containing head motion to obtain an output sequence containing extreme head motion. Finally, the natural 3D face animation under extreme head motion is presented in combination with the input audio. The quantitative and qualitative results show that our method outperforms current state-of-the-art methods. And stabilizes the non-area region while maintaining the appearance of extreme head motion.
Nonlinear Stefan problem for one-phase \ generalized heat equation with heat flux and convective boundary condition
Authors: Nauryz Targyn 
Published: November 2022

Abstract
In this article we consider a mathematical model of an initial stage of closure electrical contact that involves a metallic vaporization after instantaneous exploding of contact due to arc ignition with power $P_0$ on fixed face $z=0$ and heat transfer in material with a variable cross section, when the radial component of the temperature gradient can be neglected in comparison with the axial component with heat flux and convective boundary conditions prescribed at the known free boundary $z=\alpha(t)$. The temperature field in the liquid region of such kind of material can be modelled by Stefan problem for the generalized heat equation. A similarity variable transformation is used to solve the problem, which enables us to reduce generalized heat equation to nonlinear ordinary differential equation and we have to determine temperature solution for the liquid phase and location of melting isotherm. Existence and uniqueness of the solution is proved by using the fixed point Banach theorem. The solution for two cases of thermal coefficients, in particular, constant and linear thermal conductivity are represented, existence and uniqueness for each type of solution is proved.
Mathematics Subject Classification (2010). 80A22, 80A05.
Combined plasma cell-free DNA detection and IFN-γ/TNF-α dual fluorospot assays for diagnosing active tuberculosis
Authors: Kim Ji Yeun , Koo Bonhan , Lim So Yun , Cha Hye Hee , Kim Min Jae , Chong Yong Pil , Choi Sang-Ho , Lee Sang-Oh , Kim Yang Soo , Shin Yong , Kim Sung-Han 
Published: November 2022

Abstract
Background: Present molecular and microbiologic diagnostic tests have suboptimal sensitivity for diagnosing pauci-bacillary tuberculosis (TB). We recently developed a combined molecular and immunodiagnostic test for active TB involvingdetection of cell-free DNA (cfDNA) and of IFN-γ/TNF-α release from blood. We evaluated the diagnostic performance of this new test from patients with suspected TB.
Methods: Adult patients suspected of active TB were prospectively enrolled from March 2019 to September 2021. CfDNA detection and the IFN-γ/TNF-αdual release fluorospot assay were performed using plasma and PBMC specimens. Final diagnosis of patients with suspected TB was provided by clinical category.
Results: A total of 105 patients including 54 with active TB and 51 with not-active TB were finally analyzed. The sensitivity and specificity of cfDNA detection in plasma were 67% (95% CI, 53–79) and 80% (69–92), respectively, and those of the IFN-γ/TNF-αdual release fluorospot assay of PBMCs were 80% (67–89) and 90% (79–97), respectively. The sensitivity and specificity of the combined assays were 91% (80–97) and 77% (63–87).
Conclusion: The combination of cfDNA detection and the IFN-γ/TNF-αdual release assay using blood specimens appears to be a useful adjunct test for the diagnosis of active TB.
Factors influencing blue-collar workers’ participation in Worksite Health Promotion Programs in transport and logistics: a qualitative study using the Theoretical Domains Framework (TDF)
Authors: Damen Marc A W , Detaille Sarah I , Engels Josephine A , de Lange Annet H 
Published: November 2022

Abstract
Background
Blue-collar workers in transport and logistics report a high risk of developing chronic diseases, partly due to an unhealthy lifestyle. Worksite health promotion programs may be able to promote a healthier lifestyle, but participation by blue-collar workers in these programs is relatively low. As a result, the current study aimed to further examine psychological and contextual factors that can explain participation of blue-collar workers in these programs within the transport and logistics sector.
Methods
Semi-structured interviews were held with 32 blue-collar workers in transport and logistics in the Netherlands (94% male, 81% driver, mean age 48 (SD=11)). Interview guides were based on the Theoretical Domains Framework and were used to assess perceived determinants that influence participation. Interviews were transcribed and coded deductively to determine relevant domains, and inductively with the constant comparison method to determine key themes within and between relevant domains.
Results
From these codes seven themes emerged, namely: (1) information sometimes too abstract or too complex (2) it takes wake-up calls to make lifestyle priority, (3) autonomy and individual freedom are important, (4) distrust towards worksite health promotion programs, (5) doers instead of talkers, (6) need for personal contact and acknowledgement, and (7) little stimulation at home and at work.
Conclusions
The results revealed that the Theoretical Domains Framework proved to be a useful tool for developing the interview guide. All groups of possible determinants (capability, opportunity and motivation) could be assessed. With these insights we were able to formulate recommendations for companies to enhance the participation of blue-collar workers in worksite health promotion programs.
Benefits of PLT for Cyber-Security Training
Authors: Chowdhury Nabin , Gkioulos Vasileios , Nystad Espen 
Published: November 2022

Abstract

The security of the communication systems, digital services and functionalities of Critical Infrastructures (CI) is more important now than ever. Many of today’s energy providing infrastructures such as Smart Grids and Nuclear Power Plants rely on digitalized In- dustrial Control Systems. This, while facilitating data exchange and regular functions, has also rendered the infrastructures vulnerable to cyber-attacks. Additionally to installing security applications, ensuring that CI personnel is aware of cyber-threats and properly trained to cover all functions of their role is critical. For this purpose, several Cyber-Security (CS) training solutions have been proposed and adopted in recent years. While many advancements to CS training have been proposed in the literature, certain limitations are still present in current offerings. Current CS training and exercise offerings are often generalized to all audiences, as well as being inflexible and challenging to implement in many cases. Additionally, training participants are often not involved in the design or development of the exercises, which does not allow for tailored personaliza- tion and design of appropriate learning paths. In this work, we propose a framework for developing CS train- ing exercises based on Personalized Learning Theory (PLT) concepts. Additionally, we develop and evalu- ate two different CS exercises with two different tar- get groups developed using the framework. The results of the experiments and comparison with exercises con- ducted without using the framework show that the im- plementation of PLT concepts in the exercises had a significant effect on their effectiveness and outcome.
Modulation of defense genes and phenolic compounds in wild blueberry in response to Botrytis cinerea under field conditions
Authors: Abbey Joel , Jose Sherin , Percival David , Jaakola Laura , Asiedu Samuel K. 
Published: November 2022

Abstract
Botrytis blight is an important disease of wild blueberry [(Vaccinium angustifolium (Va) and V. myrtilloides (Vm))] with variable symptoms in the field due to differences in susceptibility among blueberry phenotypes. Representative blueberry plants of varying phenotypes were inoculated with spores of B. cinerea. The relative expression of pathogenesis-related genes (PR3, PR4), flavonoid biosynthesis genes, and estimation of the concentration of ten phenolic compounds between uninoculated and inoculated samples at different time points were analyzed. Representative plants of six phenotypes (brown stem Va, green stem Va, Va f. nigrum, tall, medium, and short stems of Vm) were collected and studied using qRT-PCR. The expression of targeted genes indicated a response of inoculated plants to B. cinerea at either 12, 24, 48 or 96 hours post inoculation (hpi). The maximum expression of PR3 occurred at 24 hpi in all the phenotypes except Va f. nigrum and tall stem Vm. Maximum expression of both PR genes occurred at 12 hpi in Va f. nigrum. Chalcone synthase, flavonol synthase and anthocyanin synthase were suppressed at 12 hpi followed by an upregulation at 24 hpi. The expression of flavonoid pathway genes was phenotype-specific with their regulation patterns showing temporal differences among the phenotypes. Phenolic compound accumulation was temporally regulated at different post-inoculation time points. M-coumaric acid and kaempferol-3-glucoside are the compounds that were increased with B. cinerea inoculation. Results from this study suggest that the expression of PR and flavonoid genes, and the accumulation of phenolic compounds associated with B. cinerea infection could be phenotype specific. This study may provide a starting point for understanding and determining the mechanisms governing the wild blueberry-B. cinerea pathosystem.
Comprehensive Analysis of CNN and YOLOv5 Object Detection Model to Classify Phytomedicine Tree’s Leaf Disease
Authors: Islam Md. Ashiqul , Haque Imdadul , Rahaman Mizanur , Jahan Tanjila , Shohan Sarwar Jahan , Ahmed Md. Tanvir , Rahman Md. Mizanur , Khatun Tania 
Published: November 2022

Abstract
Phytomedicine is not only known to the poor people of East Bengal and West Bengal as a medicine but also as a beacon of hope for survival in a diseased life. In this approach, Terminalia Arjuna, Lawsonia inermis, Azadirachta indica, and Ocimum tenuiflorum Phytomedicine tree datasets. Terminalia Arjuna mainly protects gastric mucosa from oxidative damage and it makes it strong so that the stomach gets protection against ulcers. It also exhibits strong antibacterial and antimicrobial properties which help to fight against stomach infections like gastric, diarrhea, and dysentery. There are various uses of Lawsonia inermis. It is known as a powerful detoxifier and it helps to prefer healthy gum, and healthy hair and reduces arthritis pain. The flower of Lawsonia inermis can be used for headaches due to the heat of the sun. Neem is known as Phytomedicine for all diseases and the most common diseases are treated with acne, nourishing the skin, treating wounds, use to reduce dandruff and joint pain, etc. Mainly it increases immunity and provides a healthy life. Another famous Phytomedicine known as Ocimum tenuiflorum is used to treat kidney stones, alleviate fever and headaches, provide a healthy heart, healthy eye, healthy oral, and fight against acne, etc. It is also known as a big source of vitamin K. The most famous and fast object detection algorithms as YOLOv5 and Keras pre-trained models as Xception, ResNet152V2, VGG19, and InceptionResNetV2 have been developed to predict disease-affected or disease-free leaves. The implemented approach has gained a height accuracy of 97.00% from Xception and 95% accuracy from YOLOv5.
Single-site indoor fingerprint localization algorithm based on frequency domain MIMO-CSI
Authors: Wu Qiang , Chen Susu , Li Renjie , Fan Jiancun 
Published: November 2022

Abstract
Aiming at the problem of initial channel state information (CSI) data with larger error measured in indoor environment due to the frequency offset of the transceiver device, this paper studies the performance using frequency domain CSI as fingerprints in multiple-input multiple-output (MIMO) system, and proposes a single-site indoor fingerprinting localization algorithm based on multi-carrier frequency domain MIMO-CSI. Due to the problem of distortion when transforming the frequency domain channel into time domain channel based on 4G Long Term Evolution (LTE) system, this paper uses MIMO-CSI in frequency domain directly. Considering the large dimension of the initial CSI data, we adopt two different methods to reduce the dimension. Then, we analyze the reason of phase distortion in the initial CSI data and propose a linear transformation algorithm to correct the CSI phase. After that, we use the amplitude and the corrected phase on different antennas and multi-carrier in frequency domain as original fingerprint data to be trained in a back propagation (BP) neural network. Finally, the K Nearest Neighbor (KNN) algorithm is used to improve the positioning accuracy. The experimental results show that the proposed algorithm has better positioning performance compared with other positioning schemes.
Association between osteoporosis and bone metastasis of lung cancer based on opportunistic screening by low-dose computer tomography: a retrospective cohort study
Authors: Wang Caiyun , Su Lulu , Qi Xin , Liu Hongming , Shen Yu , Zou Zhi , Qi Fei , Zhang Miao , He Junya , Qu Min , Zhang Xiaolin , Zhu Jiadong , Wang Yong , Zhu Zhimin , Cheng xiaoguang , Li Yongli , Cang Shundong 
Published: November 2022

Abstract
Background: The interaction between osteoporosis-related bone microenvironment (BMD)and tumor may accelerate bone metastasis. However, the relationship between osteoporosis and lung cancer bone metastasis is unknown.
Methods: We performed opportunistic screening for osteoporosis using chest low-dose computerized tomography (LDCT) to assess a relationship between osteoporosis and bone metastases from lung cancer. We used quantitative computed tomography (QCT) software to measure spinal trabecular BMD; we evaluated the density distribution by the American College of Radiology QCT diagnostic criteria for osteoporosis. The diagnosis of bone metastases was based on imaging methods. We obtained optimal cut-off for age by X-tile analysis. Univariate and multivariate COX survival analysis was used to compare the relationship between osteoporosis and bone metastases from lung cancer, and whether age and sex had an effect on the relationship.
Results: At baseline, 401 patients with lung cancer, mean age ± standard deviation (SD) 61.7 ± 9.7 years, underwent LDCT opportunistic screening for lung cancer and osteoporosis, including 240 men (mean age ± SD 62.3 ± 9.7 years) and 161 women (mean age ± SD 60.7 ± 9.6 years). During a median follow-up of 21.3 months, 59 patients with lung cancer progressed to bone metastases. Regression analysis showed that the risk of lung cancer bone metastasis for men with osteoporosis was adjusted hazard ratios (HR) 95% confidence interval (CI)(0.27 0.14-0.50), P<0.001. After adjusting for age and sex, regression analysis showed that the lung cancer with osteoporosis for men was adjusted HR 95%CI(0.29 0.14-0.57), P<0.001 ,and greater for patients aged 63 older (adjusted HR 95%CI, 0.32 0.15-0.69 P<0.001). The progression time of bone metastases in patients with lung cancer and osteoporosis was faster, but not statistically different than the progression time of patients without osteoporosis.
Conclusion: Overall, our study showed that osteoporosis diagnosed by low-dose chest CT opportunistic screening was associated with bone metastases from lung cancer. The findings proved that osteoporosis was an important risk factor for bone metastases from lung cancer, but osteoporosis cannot accelerate the time to progression of bone metastases. Our study highlights the clinical value of screening for osteoporosis in the prevention and treatment of bone metastases from lung cancer.
Trial registration: The study approved by the Ethics Committee of the Henan Provincial 65 People's Hospital.(Ethical Approval Number: 2021 Aaron trial Examination No. (68)).
Facilitators and barriers to engaging with the DREAMS initiative among young women who sell sex aged 18-24 in Zimbabwe: a qualitative study
Authors: Machingura Fortunate , Busza Joanna , Madimutsa Gracious , Makamba Memory , Mushati Phillis , Chiyaka Tarisai , Hargreaves James , Hensen Bernadette , Birdthistle Isolde , Cowan Frances Mary 
Published: November 2022

Abstract
Background
Adolescent girls and young women are at high risk of contracting HIV and exchanging sex for financial or material support heightens their risk. In Zimbabwe, the DREAMS initiative integrated education and employment opportunities within HIV health promotion and clinical services for vulnerable young women, including those who sell sex. While most participants accessed health services, fewer than 10% participated in any social programmes.
Methods
We conducted semi-structured qualitative interviews with 43 young women aged 18–24 to understand their experiences of engaging with the DREAMS programme. We purposively sampled participants for diversity in level of education, type and location of selling sex. We analysed the data by applying the Theoretical Domains Framework to explore facilitators and barriers to engaging with DREAMS.
Results
Eligible women were motivated by hopes of escaping poverty, and their longer-term engagement was sustained through exposure to new social networks, including friendships with less vulnerable peers. Barriers included opportunity costs and expenses such as transport or equipment required for job placements. Participants also described pervasive stigma and discrimination related to their involvement in selling sex. Interviews highlighted the young women’s struggles in a context of entrenched social and material deprivation and structural discrimination that hindered their ability to take up most of the social services offered.
Conclusions
This study demonstrates that while poverty was a key driver of participation in an integrated package of support, it also constrained the ability of highly vulnerable young women to benefit fully from the DREAMS initiative. Multi-layered HIV prevention approaches such as DREAMS that seek to alter complex and longstanding social and economic deprivation address many of the challenges faced by YWSS but will only succeed if the underlying drivers of HIV risk among YWSS are also addressed.
Uncertainty Driven Active Learning of Coarse Grained Free Energy Models
Authors: Duschatko Blake , Vandermause Jonathan , Molinari Nicola , Kozinsky Boris 
Published: November 2022

Abstract
Coarse graining techniques play an essential role in accelerating molecular simulations of systems with large length and time scales. Theoretically grounded bottom-up models are appealing due to their thermodynamic consistency with the underlying all-atom models. In this direction, machine learning approaches hold great promise to fitting complex many-body data. However, training models may require collection of large amounts of expensive data. Moreover, quantifying trained model accuracy is challenging, especially in cases of non-trivial free energy configurations, where training data may be sparse. We demonstrate a path towards uncertainty-aware models of coarse grained free energy surfaces. Specifically, we show that principled Bayesian model uncertainty allows for efficient data collection through an on-the-fly active learning framework and open the possibility of adaptive transfer of models across different chemical systems. Uncertainties also characterize models' accuracy of free energy predictions, even when training is performed only on forces. This work helps pave the way towards efficient autonomous training of reliable and uncertainty aware many-body machine learned coarse grain models.