bluuebunny/crossref_metadata_2025_split huggingface dataset:
Host Age Structure Defines Interactions with Pathogens: Grandparent Effect under Collaboration and Virulent Mutualism under Competition
Authors: Portner Carsten O.S. , Rong Edward G. , Ramirez Jared A. , Wolf Yuri I. , Bosse Angelique P. , Koonin Eugene V. , Rochman Nash D. 
Published: August 2022

Abstract
Background: Symbiotic relationships are ubiquitous in the biosphere. Inter-species symbiosis is impacted by intra-specific distinctions, in particular, those defined by the age structure of a population. Older individuals compete with younger individuals for resources despite being less likely to reproduce, diminishing the fitness of the population. Conversely, however, older individuals can support the reproduction of younger individuals, increasing the population fitness. Parasitic relationships are commonly age structured, typically, more adversely affecting older hosts.Results: We employ mathematical modeling to explore the differential effects of collaborative or competitive host age structures on host-parasite relationships. A classical epidemiological compartment model is constructed with three disease states: susceptible, infected, and recovered. Each of these three states is partitioned into two compartments representing young, potentially reproductive, and old, post-reproductive, hosts, yielding 6 compartments in total. In order to describe competition and collaboration between old and young compartments, we model the reproductive success to depend on the fraction of young individuals in the population. Collaborative populations with relatively greater numbers of post-reproductive hosts enjoy greater reproductive success whereas in purely competitive populations, increase of the post-reproductive subpopulation reduces reproductive success. However, in competitive populations, virulent pathogens preferentially targeting old individuals can increase the population fitness.Conclusions: We demonstrate that, in collaborative host populations, pathogens strictly impacting older, post-reproductive individuals can reduce population fitness even more than pathogens that directly impact younger, potentially reproductive individuals. In purely competitive populations, the reverse is observed, and we demonstrate that endemic, virulent pathogens can oxymoronically form a mutualistic relationship with the host, increasing the fitness of the host population. Applications to endangered species conservation and invasive species containment are discussed.
A novel method for localization and tracking in NLOS environments of coal mines
Authors: Hu Qingsong , Cai Xueting , Li Shiyin , Sun Yanjing 
Published: August 2022

Abstract
The performance of target localization and tracking in coal mines is seriously affected by non-line-of-sight (NLOS) propagation. This paper proposes a new method to solve this problem. First, we introduce the NLOS error vector and the correction factor vector, and determine whether there is NLOS propagation through the variance of the measured value. Then the improved Chan method is proposed to decrease the NLOS error of localization results and enhance the localization accuracy. To track moving objects, we proposed ChopThin resampling-based particle filter(CTPF) algorithm to decrease the tracking error whose observed value are the corrected distance difference during localization. It ensures the effective number of effective particles and their diversity by using the ChopThin resampling to mitigate the adverse effects of the particle degeneracy. Besides, a threshold is set to decide whether to resample to reduce the amount of computation. Simulation results show that the improved Chan localization method proposed in this paper can suppress most of the NLOS errors and improve positioning accuracy, and the proposed CTPF has smaller tracking error than the traditional resampling filter algorithm.
AES Algorithm using Dynamic Shift Rows, Sub Bytes and Mix Column Operations for Systems Security wih Optimal Delay
Authors: K Gavaskar , S Ragupathy U , G Ravivarma , S Priyadharshan P 
Published: August 2022

Abstract
In the digital world, all the transmitted data is vulnerable and prone to attack. To reduce the vulnerability, security is needed for the data. The security of the data can be enhanced by implementing cryptographic techniques. Thus, the sender and the receiver can only view the data by implementing cryptography, whereas a third party cannot intervene. Cryptographic algorithms are used in the IoT, online banking, Web servers, etc. The Advanced Encryption Standard (AES) is symmetric-key cryptography; it has the same key for both the encryption and decryption process. Each step in the AES algorithm is modified by using the key generated for each round, so each step of the AES is made key-dependent. This gives the dynamic AES algorithm. However, the delay and area are comparatively higher than the traditional method. Thus, the proposed method involves combining two steps, the sub-byte transformation and shifting rows. By doing this, the registers used to store the sub-byte data are removed. Thus, eliminating registers leads to less area consumption. Simulation is done using Verilog HDL in ModelSim and the synthesis is done in Xilinx Design Suite.
Whole genome analysis of Comamonas sp. USTBZA1 for biodegrading diethyl phthalate
Authors: Zhao Zhenzhen , Liu Chao , Xu Qianqian , Song Meijie , Yan Hai 
Published: August 2022

Abstract
Extensive use of phthalic acid esters (PAEs) as plasticizer causes diffusion into the environment, which posed a great threat to mankind. In the present study, one promising bacterial strain for biodegrading diethyl phthalate (DEP) was successfully isolated from activated sludge and characterized as Comamonas sp. USTBZA1 based on 16S rRNA sequence analysis. Under the optimal conditions of pH 7.5, 30℃ and inoculum volume ratio of 6%, initial DEP of 50 mg/L could be completely biodegrade by strain USTBZA1 within 24 h which conformed to the Gompertz model. Based on Q-TOF LC/MS analysis, monoethyl phthalate (MEP) and phthalic acid (PA) were identified as the metabolic products of DEP biodegradation by USTBZA1. Furthermore, the whole genome of Comamonas sp. USTBZA1 was analyzed to excavate PAEs catabolic genes in stain USTBZA1. There were 3 and 41 genes encoding esterase/arylesterase and hydrolase respectively which could involve in PAEs hydrolysis, and two genes regions (pht34512 and pht4253) were responsible for the conversion of PA to protocatechuate (PCA), and two genes regions (ligCBAIKJ) are involved in PCA metabolism in USTBZA1. These results substantiated that Comamonas sp. USTBZA1 had potential application in the DEP bioremediation.
Association of different doses of curcumin with preadipocyte-adipocyte differentiation and inflammatory status
Authors: Çetinalp Pınar , Değirmencioğlu Sevgin , Küçük Sevda Tanrıkulu , Seyithanoğlu Muhammed , İyidoğan Yıldız Öner , Koçak Hikmet 
Published: August 2022

Abstract

Human adipose tissue is involved in fat storage and also plays a role in the immune response. Curcumin (CUR), a natural polyphenol is suggested to supress adipocyte differentiation in the early stage by inhibiting secretion of some regulators and the inflammatory cytokines and by activating the secretion of antiinflammatory cytokines. Our aim in this research was to examine the molecular pathways of the inhibitory effects of different doses of curcumin (0.5 µM, 5 µM, 10 µM, 20 µM, 50 µM) on the preadipocyte-adipocyte differentiation and the anti-inflammatory effect of curcumin for preventing adipocyte related oxidative and inflammatory status. Differentiation of cells was performed using Oil red O, mRNA expression levels of adiponectin, CCAAT/enhancer binding proteinα (C/EBPα), cyclooxygenase-2 (COX-2), interleukin-6 (IL-6), leptin, Nuclear Factor kappa B1 (NFκB1), peroxisome proliferator-activated receptor gamma (PPARγ), sirtuin-1 (SIRT-1), tumor necrosis factor-α (TNF-α), transient receptor potential vanilloid receptor1 (TRPV1), uncoupling protein2 (UCP2), vasculer endothelial growth factor-A (VEGF-A), vascular endothelial growth factor receptor I (VEGF-RI), VEGF-RII were evaluated in preadipocytes and adipocytes. Curcumin suppressed the differentiation of preadipocyte to adipocytes, decreased the release of proinflammatory cytokines, but it did this by regulating C/EBPα and PPARγ gene expressions outside the NF-κB pathway. Curcumin effectively suppressed adipogenic transcription factors and also adipocyte differentiation at all doses between 0.5–50 µM, but showed its anti-inflammatory effect especially in the application of curcumin of 50 µM.
Hypothalamic paraventricular nucleus hydrogen sulfide exerts antihypertensive effects in spontaneously hypertensive rats by attenuating oxidative stress via the Nrf2 pathway
Authors: Xia Wen-Jie , Yu Xiao-Jing , Liu Kai-Li , Wang Xiao-Min , Yang Yu , Meng Tingting , Qiao Jin-An , Zhang Nianping , Sun Yao-Jun , Kang Yu-Ming 
Published: August 2022

Abstract
Hydrogen sulfide (H2S) is widely distributed throughout the nervous system with various antioxidant and anti-inflammatory properties. Increased reactive oxygen species and inflammation in the hypothalamic paraventricular nucleus (PVN) are involved in the pathophysiology of hypertension. But it is unclear how H2S in PVN affects hypertension. Our study used spontaneously hypertensive rats (SHR) and control Wistar Kyoto (WKY) rats, microinjected with AAV-CBS (cystathionine beta-synthase overexpression) or AAV-ZsGreeen in the bilateral PVN; or simultaneously injected with virus-carrying nuclear factor erythroid 2-related factor 2 (Nrf2)-shRNA. We found that AAV-CBS increased H2S in the PVN, and that blood pressure, neuronal activation, oxidative stress, and inflammation of PVN were all substantially reduced. In addition, PVN endogenous H2S activated Nrf2 and corrected the PVN's unbalanced of excitatory and inhibitory neurotransmitters. However, Nrf2 knockdown in the PVN was similarly observed to abolish the beneficial effect of H2S on hypertension. These results suggest that PVN endogenous H2S can ameliorate hypertension through Nrf2-mediated antioxidant and anti-inflammatory effects.
The Clinicopathological Features of Low-Grade Epilepsy-Associated Glioneuronal Tumors with CD34 Expression and BRAF Mutation
Authors: Xie Mingguo , Wang Xiongfei , Qiao Jiao , Zhou Jian , Guan Yuguang , Li Tianfu , Qi Xueling , Luan Guoming 
Published: August 2022

Abstract
Purpose
The aim of the study was to evaluate the clinicopathological features, as well as the surgical prognosis, of epilepsy-associated glioneuronal tumors (GNT) with CD34 expression and BRAF mutation.
Methods
Clinical data of patients who underwent epilepsy surgery for GNT were retrospectively studied. Univariate and multivariate analyses were performed to evaluate the correlations of clinical and pathological factors with molecular markers of CD34 expression and BRAFV600E mutation in GNT.
Results
A total of 247 patients with GNT had immunohistochemical detection of CD34 expression (CD34 positive vs. negative: 198/49), and among them, 102 patients had immunohistochemical detection of BRAFV600E mutation (BRAF positive vs. negative: 59/43). Univariate analysis found that tumor types (P < 0.001), patient population (P = 0.015), seizure aura (P = 0.007), drug-resistant epilepsy (P = 0.036), concordance of ictal electroencephalogram (EEG) findings (P = 0.032), surgical resection extent (P = 0.045), tumor location (P = 0.007) and duration of epilepsy (P = 0.027) were related to CD34 expression, and that concordance of ictal EEG findings (P = 0.031) and age at surgery (P = 0.015) were related to BRAFV600E mutation. In addition, history of generalized tonic-clonic seizure (HR = 0.12; P = 0.035), drug-resistant epilepsy (HR = 0.13; P = 0.030) and concordance of interictal EEG findings (HR = 8.01; P = 0.039) were associated with tumor progression-free survival (PFS). However, CD34 expression or BRAFV600E mutation in GNT was not associated with surgical outcomes of seizure control and tumor PFS.
Conclusion
The CD34 expression or BRAFV600E mutation in GNT may partly influence the distribution of clinicopathological features of patients with epilepsy, but they may be not able to predict the surgical prognosis of seizure outcome and tumor recurrence.
Time-of-Flight spectroscopy for laser-driven proton beam monitoring
Authors: Reimold Marvin , Assenbaum Stefan , Bernert Constantin , Beyreuther Elke , Brack Florian-Emanuel , Karsch Leonhard , Kraft Stephan , Kroll Florian , Löser Markus , Nossula Alexej , Pawelke Jörg , Püschel Thomas , Schlenvoigt Hans-Peter , Schramm Ulrich , Umlandt Marvin Elias Paul , Zeil Karl , Ziegler Tim , Metzkes-Ng Josefine 
Published: August 2022

Abstract
Application experiments with laser plasma-based accelerators (LPA) for protons have to cope with the inherent fluctuations of the proton source. This creates a demand for non-destructive and online spectral characterization of the proton pulses, which are for application experiments mostly spectrally filtered and transported by a beamline. Here, we present a scintillator-based time-of-flight (ToF) beam monitoring system (BMS) for the recording of single-pulse proton energy spectra. The setup’s capabilities are showcased by characterizing the spectral stability for the transport of LPA protons for two beamline application cases. For the two beamline settings monitored data of 122 and 144 proton pulses collected over multiple days were evaluated, respectively. A relative energy uncertainty of 5.5 % (1σ) is reached for the ToF BMS, allowing for a Monte-Carlo based prediction of depth dose distributions, also used for the calibration of the device. Finally, online spectral monitoring combined with the prediction of the corresponding depth dose distribution in the irradiated samples is demonstrated to enhance applicability of plasma sources in dose-critical scenarios.
XIST Regulates Breast Cancer Stem Cells by Activating Proinflammatory IL-6 Signaling
Authors: Ma Yuxi , Zhu Yongyou , Shang Li , Qiu Yan , Shen Na , Song Qingxuan , Li Jun , Wicha Max S. , Luo Ming 
Published: August 2022

Abstract
Background
Aberrant expression of XIST, a long noncoding RNA initiating X chromosome inactivation (XCI) during early embryogenesis, is a common feature of breast cancer (BC). However, the roles of post-XCI XIST in breast carcinogenesis remain elusive.
Methods
In this study, we examined the expression of XIST in human BC cell (BCC) lines across the spectrum of BC subtypes. We then investigated the effect of knockdown (KD) of aberrantly expressed XIST in luminal and triple-negative (TN) BCCs on tumor growth, cancer stem cell (CSC) activities, and global gene expression. We identified the most significantly altered genes and pathways in ALDH− bulk tumor cells and ALDH+ CSCs upon XIST KD and validated the roles of these genes in regulating ALDH+ epithelial (E) versus CD24−/loCD44+/hi mesenchymal (M) CSCs. Lastly, we conducted miRNA array and luciferase reporter assays to define the molecular mechanisms of XIST in CSC regulation.
Results
Doxycycline (DOX) induced XIST KD markedly inhibits spheroid/colony forming capacity, tumor growth and tumor-initiating potential. This phenotype is attributed to impaired E-CSC in luminal and E- and M-CSC activities in TN BCCs. Gene expression profiling demonstrates that XIST KD most significantly affects cytokine-cytokine receptor interactions, resulting in markedly suppressed expression of proinflammatory cytokines IL-6 and IL-8 in the bulk of tumor cells. Exogenous IL-6, but not IL-8, rescues the reduced sphere-forming capacity and proportion of ALDH+ CSCs in luminal and TN BCCs following XIST KD. This suggests a mechanism whereby XIST regulates IL-6 production by bulk tumor cells, which then acts in a paracrine manner on ALDH+ CSCs that display elevated IL-6 receptor (IL6R) expression. XIST functions as a molecular sponge for MicroRNA let-7a-2-3p to derepress IL-6 expression, which in turn promotes self-renewal of ALDH+ CSCs by inducing STAT3 activation and expression of key CSC factors including c-MYC, KLF4 and SOX9.
Conclusions
This study supports a novel role of XIST by derepressing let-7 controlled paracrine IL-6 proinflammatory signaling to promote CSC self-renewal.
WITHDRAWN: Explaining the Conceptual Model of the Architectural Process Method Inspired by Nature
Authors: Olia Shermin , Habib Farah , Shahcheraghi Azadeh 
Published: August 2022

Abstract
Nature strategies have a constructive effect on the sustainable solution, but due to the complexities of nature's strategies and its interdisciplinary character, we need to know the process of architectural creation with framing inspired by nature. We need to change behavior and develop sustainable thinking as an intellectual system, which is possible by taking advantage of the rich source of nature knowledge. Considering the scale of biological information, the lack of ease of recognizing and applying nature's strategies, it requires the conceptual model. The main question is to establish a clear connection between the mentioned concepts, discover the effective components in the design process, which creates new paths to reach innovative designs inspired by nature. The research shows that: the biological framing of the architectural creation process begins based on the design problem solving approach. Biological knowledge and information, in addition to affecting the quality and capability of the product, also causes changes in the architectural creation process. The most important effect of it is to change the type of attitude in design in order to achieve harmony and create a balance between the human made environment and nature, increasing productivity and achieving stability, not reducing the amount of instability.
Similar Classes Latent Distribution modelling-based Oversampling Method for Imbalanced Image Classification
Authors: Ye Wei , Dong Minggang , Wang Yan , Gan Guojun , Liu Deao 
Published: August 2022

Abstract
Learning an unbiased classifier from imbalanced image datasets is achallenging task, since the classifier may strongly bias towards majorityclasses. To address this issue, some deep generative models-basedoversampling methods have been proposed. However, most methods paylittle attention to the decision boundary, which may contribute tiny tolearning an unbiased classifier. In this paper, we focus on the decisionboundary and propose a similar classes latent distribution modellingbasedoversampling method.Specifically, first, we model each class asdifferent von Mises-Fisher distributions, thereby aligning feature learningwith the class distributions. Furthermore, we develop a distanceminimization loss function, which makes similar classes closer in latentspace. The generator can learn more shared latent features from thedecision region. In addition, we propose a boundary sampling strategy,which uses latent variables between similar classes to generateboundary samples for data balancing. Experiments on four imbalancedimage datasets show that the proposed method achieves promisingperformance in terms of Recall, Precision, F1-score and G-mean.
A Reinforcement Learning based tool for non-parametric population pharmacokinetics workflow optimization
Authors: Otalvaro Julian D , Yamada Walter M , Hernandez Alher M , Zuluaga Andres F , Chen Rong , Neely Michael N 
Published: August 2022

Abstract
Background: The building of population pharmacokinetic models can be described as an iterative process in which given a model and a dataset, the pharmacometrician performs introduces some changes, then perform an evaluation and based on the predictions obtained performs further optimization. This process (perform an action, witness a result, optimize your knowledge) is a perfect scenario for the implementation of Reinforcement Learning algorithms. In this paper we present the conceptual background and a implementation of one of those algorithms aiming to show pharmacometricians how to automate (to a certain point) the iterative model building process. Methods: We present the selected discretization for the action and the state space. SARSA was selected as the RL algorithm to use, configured with a window of 1000 episodes with and a limit of 30 actions per episode. Under the hood we used the Non-Parametric Optimal Design (NPOD) to perform the parameter optimization. Results: The RL based agent managed to obtain the same likelihood and number of support points, with a distribution similar to the reported in the original paper. The total amount of time used by the train the agent was 5.5h, although we think this time can be further improved. Conclusions: It is possible to automatically find the structural model that maximizes the final likelihood for an specific pharmacokinetic dataset by using Reinforcement Learning (RL) algorithm. The framework provided could allow the integration of even more actions i.e: add/remove covariates, non-linear compartments or the execution of secondary analysis. Many limitations were found while performing this study but we hope to address them all in future studies.
Distributional effect of international remittances on household expenditure: Evidence from Cameroon
Authors: MEKA'A BERNARD COSMAS , BITA CHARLES ALAIN , NOUFELIE ROMUS TCHUELACHUE 
Published: August 2022

AbstractIn this study, we examine the distributional effect of international remittances on household expenditures in Cameroon. We define non-poor (poor) and recipient households as those who have access to remittances and allocate a large (small) proportion of their budgets on health, education and/or food. Following this definition, our study uses the quantile regression method and migration observatory data from the Africa and Caribbean (2012) survey, to empirically examine the relation. Results show however that remittances negatively affect the three expenditure items, but only the relation between remittances and food expenditures show statistically significant outcomes. In respect to the quantile distribution method, we find a negative average effect of remittances on food expenditure. In addition, the effect of remittances on the expenditure of less poor household is positive at a large magnitude. This result hence suggests increased economic inequalities resulting from increased remittances. Our finding further confirm the hypothesis stipulating that: adverse distributional effect of remittances depend on household ability to finance the migration cost. We therefore agree with already existing conclusions in the economic literature.
Grading Ethiopian Coffee Raw Quality Using Image Processing Techniques.
Authors: Bedaso Muktar , Meshesha Million , Diriba Chala 
Published: August 2022

Abstract
Coffee is a beverage obtained from cherry, the fruit of coffee plant. Grading serves as a process for controlling the quality of an agricultural commodity so that buyer and seller can do business without personally examining every lot sold. This study attempts to apply image processing techniques towards sample coffee raw quality value Grading. A total of 145 image datasets and 10,000 coffee beans were used from different grade of coffee from ECX Jimma center. The experimental research design was employed. ImageJ tool and Matlab programming language were used. For image preprocessing Gaussian filter to remove noise, contrast enhancement method to enhance the quality of coffee bean image, Normalization and Binarization by thresholding 8-bit images algorithm to separate image into region in image segmentation process were used. Techniques and algorithms such as ANN, SVM and KNN were used in this study. For the purpose of computing the grading accuracy of datasets, 80% of total dataset were used for training the model and the remaining 20% of dataset were used for testing. The major challenges during conducting this study were keeping the best quality control environment when acquiring images, extracting best features of HSB color feature and the homogeneity of coffee bean color features. Hence, appropriate selection of image processing and classification modules paves the way for higher accuracy in the higher-level process for decision making.