bluuebunny/crossref_metadata_2025_split huggingface dataset:
Chemokine expression predicts T cell-inflammation and improved survival with checkpoint inhibition across solid cancers
Authors: Zogopoulos George , Romero Joan Miguel , Titmuss Emma , Wang Yifan , Vafiadis James , Pacis Alain , Jang Gun Ho , Zhang Amy , Golesworthy Bryn , Lenko Tatiana , Williamson Laura , Grünwald Barbara , O'Kane Grainne , Jones Steven , Marra Marco , Wilson Julie , Gallinger Steven , Laskin Janessa 
Published: January 2023

Abstract
Immune checkpoint inhibitors (ICI) are highly effective in specific cancers where canonical markers of antitumor immunity are used for patient selection. Novel predictors of T cell-inflammation are needed to identify ICI-responsive tumor subsets in additional cancer types. We investigated associations of a 4-chemokine expression signature (c-Score: CCL4, CCL5, CXCL9, CXCL10) with metrics of antitumor immunity across tumor types. Across cancer entities from The Cancer Genome Atlas, subgroups of tumors displayed high expression of the c-Score (c-Scorehi) with increased transcriptional hallmarks of the cancer-immunity cycle, while high tumor mutation burden (TMB) was associated with only a subset of c-Scorehi tumors. Among 82 patients treated with ICIs, the c-Scorehi subgroup exhibited longer median time to progression (103 versus 72 days, P=0.012) and overall survival (382 versus 196 days, P=0.038), and the c-Score outperformed TMB for overall survival prediction. Taken together, the c-Score identifies patients with hallmarks of T cell-inflammation and response to ICI treatment across cancer types.
A Novel Edge-Inspired Depth Quality Evaluation Network for RGB-D Salient Object Detection
Authors: Xu Kun , Guo Jichang 
Published: January 2023

Abstract
Recently, the pair of RGB images and depth images, which is denoted as RGB-D images, are introduced to improve their performances of Salient Object Detection(SOD), because one of the pairs may stand out at least in one modality. However, most existing State-Of-The-Art(SOTA) methods still suffer from dilemma. Firstly, the edges of predicted salient object are blurry. Secondly, how to integrate RGB-D images effectively still needs be explored. Thirdly, the quality of depth images have a strong impact on the performance of SOD so that the selection of depth images is worthy of exploring. To address the problems, in this paper, we propose a Edge-Inspired Depth Quality Evaluation Network(EDQNet), which evaluates the quality of the depth images based on the edge of ground truth, the edge of depth images and the predicted edge. More specifically, the Depth Quality Evaluation Module(DQEM) includes two parts: the depth decider and the depth aggregator. The former judges the quality of the depth images while the latter produces the weighted depth features. Then, the edge Detection Module(EDM) is proposed to predict the edge of salient object, producing the edge features. In addition, features from VGG backbone, edge features and the depth features are integrated by our Multi-Modality Feature Fusion(MMF) by using a series of composition of Hybrid Dilated Convolution(HDC). Moreover, the integrated features are fused by the Three-feature Interactive Module(TIM), Double-feature Interactive Module(DIM) and deconvolution to predict the final salient map. Our experiments on four RGB-D datasets demonstrate that our proposed EDQNet outperforms previous SOTA RGB-D SOD.
Symplectic integration for Hamiltonian stochastic differential equations driven by additive L´evy noise
Authors: Zhan Qingyi , Duan Jinqiao , Li Xiaofan 
Published: January 2023

Abstract
This paper proposes a general symplectic Euler scheme for a class of Hamiltonian stochastic differential equations driven by L´evy noise in the sense of Marcus form. The convergence of the symplectic Euler scheme for this Hamiltonian stochastic differential equations is investigated. Realizable numerical implementation of this scheme is also provided in details. Numerical experiments are presented to illustrate the effectiveness and superiority of the proposed method by the simulations of its orbits, symplectic structure and Hamiltonian.
Can carbon emission trading improve energy efficiency? Evidence from clean energy transition
Authors: Xie Yunyan , Guo Yifan , zhao xing 
Published: January 2023

Abstract
Improving energy efficiency is essential to achieving sustainable development and promoting energy transition. Using provincial panel data of 30 regions in China from 2011 to 2020, this paper analyzes the impact of carbon emission trading on energy efficiency from the perspective of clean energy transition. The results are as follows: Carbon trading policy has a significant improvement effect on energy efficiency, and it remains valid after a series of robustness tests. Mechanism test shows an effective intermediary way of clean energy transition, in which the carbon emission policy reduces coal consumption intensity, thus optimizing energy structure and ultimately raising energy efficiency. In regions with low level of economic development and high level of marketization, carbon emissions trading plays a more significant role in improving energy efficiency. This paper helps to provide a reference for governmental departments as they optimize their strategy for promoting the construction of a national carbon emissions trading market and improving energy efficiency.
Divergent patterns and assembly processes of soil fungal abundant and rare communities along an elevational gradient in subalpine areas of Southwest China
Authors: Yang Fan , Long Chunyan , Chen Qiong , Cheng Xiaoli 
Published: January 2023

Abstract
Aim
Understanding the patterns and assembly processes of microbial communities along an elevational gradient remains largely debated.
Methods
We examined soil fungal abundant and rare communities and the underlying drives across a wide elevation from 2100-3950 m (a. s. l.) along the Yulong Mountain of Southwest China.
Results
We found the abundant and rare taxa were divergent in diversity, and only the α diversity of abundant taxa followed a humpback trend and peaked at 2900 m, despite the β diversity were significantly dependent on elevation gradients. Soil fungal abundant and rare taxa showed significant elevation-decay relationship, with more dispersal limitation to abundant taxa than that of rare taxa. Along the elevational gradients, the assembly of abundant fungal sub-communities were governed by combined effect of both environmental factors (soil nitrogen and potassium, soil temperature) and dispersal limitation, whereas the rare fungal sub-communities were merely dominated by stochastic processes (ecological drifts). Network modules analysis revealed higher functional redundancy in rare fungal sub-communities and this influence reinforced neutrality, and hence impelled rare fungal more susceptible to drift.
Conclusion
Our results suggested the divergent pattern and assembly process for soil fungal abundant and rare fungal taxa along an elevational gradient emphasized the stochastic process in fungal communities’ assembly, especially for low abundant taxa.
Integrated assessment of landslide susceptibility in the Kalaleh Basin, Golestan Province, Iran using novel SVR-GOA ensemble validated with BRT, ANN, and elastic net models
Authors: Zhu Quanpeng , Arabameri Alireza , santosh mum , Egbueri Johnbosco , Agbasi Johnson 
Published: January 2023

Abstract

Landslides cause severe environmental problems, such as severe damages to infrastructures (i.e., bridges, roads, network masts, and buildings) and agricultural lands, across many parts of the world. Unfortunately, a high degree of accuracy in landslide mapping and prediction is still challenging due to the complicated interactions of many factors. The goal of this study was to create and introduce a new ensemble model (support vector regression–grasshopper optimization algorithm (SVR–GOA)) validated alongside artificial neural network (ANN), boosted regression tree (BRT), and elastic net models for landslide susceptibility modeling taking the Kalaleh Basin in Iran as a case study. For this objective, a total of 140 landslides were considered and 16 conditioning factors used to construct a geographic database. Subsequently, variance inflation factor and tolerance indices were used to test the multicollinearity of the hazard conditioning variables. The relative significance of these factors and their connections to the locations of the landslides were determined using random forest. The development and validation of the four landslide models, SVR-GOA, ANN, BRT, and elastic net, were then performed. This study is the first to implement the SVR-GOA in landslide mapping. The effectiveness of the models was evaluated using area under the curve (AUC), kappa, and root mean squared error values. The outcome indicated that the lithology, slope degree, rainfall, topography position index, topography wetness index, surface area, and landuse/landcover were the most influential conditioning factors. All of the models provided predictions with good degree of fit, with the SVR-GOA performing better than others. The models performed in the order, at validation phase: SVR-GOA (AUC = 0.930) > ANN (AUC = 0.833) > BRT (AUC = 0.822) > elastic net (AUC = 0.726). Our novel approach employing the SVR-GOA ensemble in landslide mapping would help advance landslide research on regional, national, and global scales.
The protective effect of CD200 on hemorrhage/sepsis-associated acute kidney injury
Authors: Geng Yuanyuan , Sun Leilei , Tang Weiqing , Zhang Yunhe , Hu Baoji , Pan Mengzhi 
Published: January 2023

Abstract
Background Acute kidney injury is a serious complication of morbidity and mortality with critically ill patients in short and long-term. Severe trauma patients especially followed infection will induce acute kidney injury.
Methods C57BL and C57BL background CD200 deficiency mice were applied to undergoing the operation of cecal ligation and puncture following hemorrhage. The model was used to simulate the process of shock patients followed infection, which associated with acute kidney injury clinically. Blood and kidney tissues were harvested 24 h after hemorrhage/cecal ligation and puncture. CD200 expression on neutrophils and monocytes in blood was stained and measured via flow cytometry analysis. Serum creatinine and blood urea nitrogen were measured according to the manufacturer’s instruction. Cytokines and counterpart RNA expression were detected via ELISA and RT-PCR, respectively. The severity of kidney injury was assessed by pathologists. The protein level of neutrophil gelatinase-associated lipocalin and high mobility group 1 was measured via western blot.
Outcome CD200 expression was elevated on neutrophils and monocytes in blood. Furthermore, the severity of kidney injury of histology, assessed by pathologists, was much aggravated on acute kidney injury and even exacerbated on CD200 deficiency mice. The levels of serum creatinine and blood urea nitrogen were all increased in CD200 deficiency mice. Cytokines of IL-6 and TNF-α increased in acute kidney injury and even aggravated in CD200 deficiency mice, but IL-10 was demonstrated the reversed trend. The consistent trend of RNA expression of cytokines including IL-6, TNF-α and IL-10 was corroborated via RT-PCR. As western blot demonstrated, the protein level of neutrophil gelatinase-associated lipocalin was increased and high mobility group 1 decreased in CD200 deficiency mice.
Conclusion CD200 may be involved in the development of hemorrhage/cecal ligation and puncture associated acute kidney injury. It may be speculated that CD200 plays a protective effect in acute kidney injury potentially through inhibiting neutrophil gelatinase-associated lipocalin and activating high mobility group 1 signaling pathway.
The impact of information quality of antimicrobial susceptibility test report on the rational antimicrobial use
Authors: Wei Ming , Wang Yanting , Zhang Xinping , Xu Xiaojun , Li Yan 
Published: January 2023

Abstract
Background
Antimicrobial susceptibility test (AST) report was important for rational antimicrobial use. However, the reference value of AST report was sometimes limited due to poor information quality (IQ). This study aimed to measure the IQ of AST and evaluate the impact of IQ of AST report on rational antimicrobial use as a reference for antimicrobial therapy.
Methods
The retrospective study included data of AST report, antimicrobials prescribed after reporting AST results and related inpatient information. The inclusion criteria of the AST report included three conditions: 1. The AST reports were from inpatients with diagnosis of infection. 2. The bacteria were extracted from a sterile-site specimen. 3. The interpretive categories (ie. sensitive, intermediary or resistance) were firstly reported during one hospitalization. The IQ of AST report was measured by the total IQ and IQ of completeness, usefulness, accuracy and consistency. The rational antimicrobial use was measured by the antimicrobial adherence to the interpretive categories of AST report. Fractional logit regression model (FLRM) was chosen to evaluate the impact of IQ on the rational antimicrobial use.
Results
The median of the total IQ, completeness, usefulness, accuracy and consistency were 0.7345, 0.6082, 0.9167, 0.8966 and 1.0000, respectively. The results of FLRM showed that usefulness, accuracy and consistency had significant positive impacts on the rational antimicrobial use (β = 4.220, P < 0.01; β = 3.987, P < 0.01; β = 0.511, P < 0.05, respectively), while the total IQ and completeness had no statistically significant impacts on the rational antimicrobial use (β=-0.820, P > 0.1; β=-0.793, P > 0.1, respectively).
Conclusion
This study confirmed that usefulness, accuracy and consistency performed well and had positive impacts on the rational antimicrobial use, which indicated that improving IQ especially usefulness, accuracy and consistency would make AST report play a greater role in promoting the rational antimicrobial use.
A regional-scale hydrogeological study for identifying karstic aquifers with high water resource potential in Iran
Authors: Morsali Massoud 
Published: January 2023

Abstract
This study has been carried out with the aim of identification of areas of extensive karstification and consequently groundwater resource potential carbonate rocks in Iran considering the role of the chief factors affecting karst water potential. Accordingly, 25 different data layers where interrogated in a GIS platform. Subjective karst map was developed on the basis of what is considered to be a proper combination of these factors. The most important parameters are categorized to three driving factors include chemical, physical, and hydrogeological factors. Thematic map of each parameter was prepared using geographic information system (GIS). Measuring the rate and weight of the maps was performed using analytical hierarchical process (AHP), respectively. The final output map showed different zones of groundwater prospective potential, which was divided into five grades. According to the results, of the total area of 174049 km2 of carbonate outcrops in Iran, 10.5 % belongs to grade 1 (very high degree), 15 % to grade 2 (high degree), 24.5 % to grade 3 (medium degree), 29 % to grade 4 (low degree), and 21 % grade 5 (very low degree) of karst water potential. There is a significant karst water source in the southwest, north, and north east of Iran. The highest grade is belonging to the Kopet-Dagh zone in northeast of Iran.
A Novel MCGDM Model on Dynamic COVID-waves Analysis in Indiaunder Linguistic Neutrosophic Environment
Authors: BANIK BAISAKHI , GARAI PURNIMA , ALAM SHARIFUL , CHAKRABORTY AVISHEK 
Published: January 2023

Abstract
In this research study, a dynamic multi-criteria group decision-making (MCGDM) problem in linguisticneutrosophic frame has been executed with uncertain weights prescribed on the decision-makers. Here, thenotion of dynamic MCGDM problem is introduced to synchronize the different COVID wave attacks in theIndian scenario and selection of the best preventive measure advised by various experts. In different wave surges,the outcome of the waves changes along with the nature of the corona variant. Thus the adaptation of dynamicMCGDM problem is very much relevant in this concern. Exponential aggregation operator has been fabricatedin the linguistic neutrosophic frame and TODIM (TOmada de Decisao Interativa Multicriterio) technique is usedto compile the data. Our numerical simulation and sensitivity analysis reveal that the alternative “Masking”is the best preventive measure through out all the three COVID wave scenarios in India. Finally, the resultsobtained through our method are compared with other existing techniques and it is observed that our executedtechnique is compatible and coherent with other methods with some extra flexibility and features.
The Effects of Environmental Arsenic on the Photosynthesis, Antioxidants Systems, and Biosynthesis of Pistachio Oil
Authors: Yazdanpanah-Ravari Simin , Sharifabad Hossein Heidari , Abbaspour Hossein , Iranbakhsh Alireza 
Published: January 2023

Abstract

Heavy metals adversely impact not only soil and water, but also the plants existing nearby. To investigate the impact of arsenic contamination on physiological properties, antioxidant activities, and synthesis of pistachio oil, an experiment was conducted in 2021 in a CRD. Findings proved that the amounts of arsenic in different organs, bioaccumulation coefficient (BCF), and transfer factor (TF) were different in different study areas. The amount of arsenic in roots was much higher than the leaves; the highest amount of arsenic in the leaves, roots, and fruits of the studied region was 1000 to 1200 mg/kg. The highest amounts of BCF found in the leaves and fruits were 0.11 and 0.015, respectively. The TF changes were found more frequent in pistachio leaves than its fruits. An increasing trend of changes was observed in ion losses, malondialdehyde, carotenoids and flavonoids, glutathione peroxidase activity, glutathione reductase, phenolalanine amoliase, pyrroline-5-carboxylase synthase, lipoxygenase, and linoleic fatty acid which was due to an increase in total concentrations of valretic acid. Chl a and b, protein content, reduced glutathione, ascarobate peroxidase, proline dihydrogenase, oil content, oleic acid, and palmitic acid decreased linearly. Changes to malondialdehyde, Chl a, flavonoids, and pyrroline-5-carboxylase synthase showed the highest correlations with changes in arsenic level. Generally, it was found that arsenic accumulation caused damage to the structure of proteins, cell membranes, and photosynthetic pigments of the plant. These damages, in turn, led to the activation of plant's defense mechanism and had deterrent impact on the biosynthesis of the plant's oil.
Comparison of Structured Residuals Design Techniques for actuator and sensor Fault Detection and Isolation in a Permanent Magnet DC Motor
Authors: Antic Sanja , Rosic Marko , Djurovic Zeljko , Bozic Milos 
Published: January 2023

Abstract
The reliability of actuators and sensors is an important topic in many electric motor drives. A comparison of structured residual synthesis methods for actuator and sensor fault detection and isolation (FDI) in a permanent magnet (PM) DC motor, applying two different approaches to the design of primary residuals, is presented in the paper. The first method involves a standard approach and is based on system transfer matrix synthesis. The second, more convenient approach involves the synthesis of primary residuals based on the analysis of subsystems that describe the observed system. Both methods are applicable for linear and stationary systems but were successfully applied to a laboratory system that shows nonlinear and non-stationary properties and is affected by a constant disturbance, thanks to the proposed technique of residual translation with the previous design of internal residuals. A real-time experiment performed on a laboratory setup, which consists of a DC motor, an amplifier designed in the form of a linear electronic circuit, and a Compact RIO 9075 real-time processor, is used to illustrate the drawbacks and advantages of the analyzed approaches.
Gender differences in the association of individual and contextual socioeconomic status with hypertension in 230 Latin American cities from the SALURBAL study: a multilevel analysis.
Authors: Coelho Débora Moraes , Andrade Amanda Cristina Souza , Silva Uriel Moreira , Lazo Mariana , Slesinski Claire , Quistberg Alex , Diez-Roux Ana V. , Friche Amélia Augusta Lima , Caiaffa Waleska Teixeira 
Published: January 2023

Abstract

Background:Despite global interest in gender disparities and social determinants of hypertension, research in urban areas and regions with a high prevalence of hypertension, such as Latin America, is very limited. The objective of this study was toexamine associations between the individual- and area-level socioeconomic status and hypertension in adults living in 230 cities in eight Latin America countries.Methods:In this cross-sectional study, we used harmonized data from 109,184 adults (aged 18-97 years) from the SALURBAL (Salud Urbana en America Latina/Urban Health in Latin America) project. Hypertension was assessed by self-report. The individual-, sub-city- and city-level education were used as proxies of socioeconomic status. All models were stratified by gender.Results:While individual-level education was positively associated with higher odds of hypertension among men (university education or higher versus less than primary: Odds Ratio [OR] = 1.63; 95% confidence interval [CI] = 1.45-1.83) the reverse was true among women (university education or higher versus lower than primary: OR = 0.66, 95%CI = 0.60-0.73), with both associations showing a dose-response pattern. For both genders, living in sub-city areas with higher educational achievement was associated with higher odds of hypertension (OR per standard deviation [SD] = 1.05, 95%CI = 1.01-1.10; OR = 1.09 per SD, 95%CI = 1.03-1.16, for women and men, respectively). The association of city-level education with hypertension varied across countries. In Peru, there was an inverse association (lower proportion of hypertension with a better education at the city level) in women and men, in other countries, no association was observed.Conclusion:The social patterning of hypertension differs by gender and by the level of analysis highlighting the importance of context- and gender-sensitive approaches and policies to reduce the prevalence of hypertension in Latin America.
CO2 flushing triggers large eruptions at open conduit volcanoes: the case of Stromboli (Italy)
Authors: Caricchi Luca , Montagna Chiara , Aiuppa Alessandro , Lages Joao Pedro Nogueira , Tamburello Giancarlo , Papale Paolo 
Published: January 2023

Abstract
Open conduit volcanoes, of which Stromboli is an emblematic example, erupt with the highest frequency on Earth1. The activity at Stromboli is characterised by frequent small explosions intercalated by larger events that pose a significant risk to locals, tourists, and scientists2,3. Thus, identifying the signs of an impending larger explosion is of outmost importance for the mitigation of volcanic hazard. Here we show that the interaction between CO2-rich fluids and magma spontaneously leads to the accumulation of volatile-rich, low density and gravitationally unstable magma at depth, without the requirement of a permeability barrier4. CO2-flushing forces the exsolution of water and the increase of magma viscosity5, which proceeds from the bottom of the magma column upward. This rheological configuration unavoidably leads to the progressive thickening of a gas-rich and low density (i.e. gravitationally unstable) layer at the bottom of feeding system. Our calculations account for gas monitoring data and provide a base to trace the approach to deeply triggered large or paroxysmal eruptions and estimate their size from continuous gas monitoring data. The model we propose for Stromboli can be applied to any other open conduit volcano globally and offers a framework to anticipate the occurrence of unexpectedly large eruptions.