mlsa-iai-msu-lab/ru_sci_bench_zho_cite_reranking huggingface dataset:
Breast cancer immunology and immunotherapy: targeting the programmed cell death protein-1/programmed cell death protein ligand-1

Historically, breast cancer has been regarded as an immunogenic “cold” tumor. However, the discovery of immune checkpoint inhibitors has made immunotherapy becoming an emerging new treatment modality for breast cancer. This review discusses the immune system, immune features of breast cancer, and the programmed cell death protein-1/programmed cell death protein ligand-1 (PD-1/PD-L1) inhibitors used in the treatment of breast cancer. High T lymphocyte infiltration and mutation burden were observed in triple-negative breast cancer and human epidermal growth factor receptor 2 positive breast cancer. Increasing breast cancer immunogenicity and modulating the tumor microenvironment has been reported to improve the therapeutic efficacy of immunotherapy. Recent clinical trials involving PD-1/PD-L1 inhibitors monotherapy in breast cancer has revealed little efficacy, which highlights the need to develop combinations of PD-1/PD-L1 inhibitors with chemotherapy, molecularly targeted therapies, and other immunotherapies to maximize the clinical efficacy. Collectively, the immunotherapy might be a promising therapeutic strategy for breast cancer and several clinical trials are still on-going.
人口老龄化对我国健康保健服务体系的挑战与对策

人口老龄化对健康保健服务体系的挑战主要体现医疗、康复和照护需求。积极应对人口老龄化,实现健康老龄化,亟须加强医养结合的实践探索和政策设计,建设医疗、照护与环境相结合的公共卫生服务体系,加强老年医学专业人才培训管理体系的建设和建立多层次医疗保障体系等方面。基于我国人口老龄化的现状和发展趋势,分析其对我国健康保健服务体系的影响,提出符合我国国情的对策与建议。
Effect of land-use changes on chemical and physical properties of soil in western Iran (Zagros oak forests)

The consequence of land-use change from forest to agriculture and other uses has become one of the world’s greatest concerns. The soil, one of the most important components of forests and containing all the required plant nutrients as soluble ions, is highly impacted by these changes. Because vast areas of the Zagros forests in western Iran have changed in use during the last few decades, the present study investigated the effects of landuse changes of forest area to agriculture, orchard, and agroforestry on soil chemical and physical properties. Soil was sampled at four land-use areas: less-disturbed forest areas (control) and agricultural, orchard, and agroforestry areas. Among each of the two forest-use areas (agroforestry and orchard), we selected five trees with similar-sized crowns and sampled under each tree crown at 0-15 and[15-30 cm depths. Five soil samples also were taken in agriculture area at each depth. The findings indicated that during land-use changes, soil sand particles decreased, and clay and silt particles of soil increased, resulting in a fine soil texture. Moreover, the amount of nitrogen (N), phosphorus (P), organic carbon (OC), and electrical conductivity (EC) of soil decreased at both depths due to the decrease in organic matter. Soil pH and magnesium (Mg) level rose during land-use change at both depths except at agricultural sites. Soil potassium (K) content decreased during agricultural use due to the elimination of tree cover. The level of K decreased only at the depth of 0-15 cm because of K dependency on parent materials. Generally, most soil nutrients were affected by plant removal in the conversion. Forest and agricultural soil are distinguishable by their properties, while land-uses such as agroforestry-orchard separated from the others. Soil nutrients were severely affected by the decrease and elimination of tree cover, plowing, and continuous harvesting, resulting in a decline in soil quality and fertility.
Comparative analysis of multi-criteria probabilistic FR and AHP models for forest fire risk (FFR) mapping in Melghat Tiger Reserve (MTR) forest

A comparative study of Frequency Ratio (FR) and Analytic Hierarchy Process (AHP) models are performed for forest fire risk (FFR) mapping in Melghat Tiger Reserve forest, central India. Identification of FFR depends on various hydrometeorological parameters (altitude, slope, aspect, topographic position index, normalized differential vegetation index, rainfall, air temperature, land surface temperature, wind speed, distance to settlements, and distance by road are integrated using a GIS platform. The results from FR and AHP show similar trends. The FR model was significantly higher accurate (overall accuracy of 81.3%, kappa statistic 0.78) than the AHP model (overall accuracy 79.3%, kappa statistic 0.75). The FR model total forest fire risk areas were classified into five classes: very low (7.1%), low (22.2%), moderate (32.3%), high (26.9%), and very high (11.5%). The AHP fire risk classes were very low (6.7%), low (21.7%), moderate (34.0%), high (26.7%), and very high (10.9%). Sensitivity analyses were performed for AHP and FR models. The results of the two different models are compared and justified concerning the forest fire sample points (Forest Survey of India) and burn images (2010-2016). These results help in designing more effective fire management plans to improve the allocation of resources across a landscape framework.
Advanced land observing satellite data to identify ground vegetation in a juniper forest, northeast Iran

Juniperus excelsa subsp. polycarpos, (Persian juniper), is found in northeast Iran. In this study, the relationship between ground cover and vegetation indices have been investigated using remote sensing data for a Persian juniper forest. Multispectral data were analyzed based on the Advanced Visible and Near Infrared Radiometer type 2 and panchromatic data obtained by the Panchromatic Remote-sensing Instrument for Stereo Mapping sensors, both on board the advanced land observing satellite (ALOS). The ground cover was calculated using field survey data from 25 sub-sample plots and the vegetation indices were derived with 5 × 5 maximum filtering algorithm from ALOS data. R2 values were calculated for the normalized difference vegetation index (NDVI) and various soil-adjusted vegetation indices (SAVI) with soilbrightness- dependent correction factors equal to 1 and 0.5, a modified SAVI (MSAVI) and an optimized SAVI (OSAVI). R~2 values for the NDVI, MSAVI, OSAVI, SAVI (1), and SAVI (0.5) were 0.566, 0.545, 0.619, 0.603, and 0.607, respectively. Total ratio vegetation index for arid and semi-arid regions based on spectral wavelengths of ALOS data with an R2 value 0.633 was considered. Results of the current study will be useful for forest inventories in arid and semi-arid regions in addition to assisting decisionmaking for natural resource managers.
Effects of climate and forest age on the ecosystem carbon exchange of afforestation

Afforestation is believed to be an effective practice to reduce global warming by sequestering large amounts of carbon in plant biomass and soil. However, the factors that determine the rate of carbon sequestration with afforestation are still poorly understood. We analyzed ecosystem carbon exchange after afforestation based on eddy covariance measurements with the aim to identify factors responsible for the rate of carbon exchange following afforestation. The results indicated that afforestation in the tropical/subtropical and temperate climate zones had greater capacities for carbon sequestration than those in boreal zones. Net ecosystem production (NEP), gross primary production (GPP) and ecosystem respiration (RE) varied greatly with age groups over time. Specifically, NEP was initially less than zero in the\10 year group and then increased to its peak in the 10-20 year group. Afforestation of varied previous land use types and planting of diverse tree species did not result in different carbon fluxes. The general linear model showed that climate zone and age of afforestation were the dominant factors influencing carbon sequestration. These factors jointly controlled 51%, 61% and 63% of the variation in NEP, GPP and RE, respectively. Compared to the strong regulation of climate on GPP and RE, NEP showed greater sensitivity to the age of afforestation. These results increase our understanding of the variation in ecosystem carbon exchange of afforestation and suggest that afforestation in subtropical and temperate areas after 20 years would yield greater carbon sink benefits than would afforestation of boreal regions.
First-principles calculation of intrinsic defect chemistry and self-doping in PbTe

Semiconductor dopability is inherently limited by intrinsic defect chemistry. In many thermoelectric materials, narrow band gaps due to strong spin–orbit interactions make accurate atomic level predictions of intrinsic defect chemistry and self-doping computationally challenging. Here we use different levels of theory to model point defects in PbTe, and compare and contrast the results against each other and a large body of experimental data. We find that to accurately reproduce the intrinsic defect chemistry and known self-doping behavior of PbTe, it is essential to(a) go beyond the semi-local GGA approximation to density functional theory,(b) include spin–orbit coupling, and(c) utilize many-body GW theory to describe the positions of individual band edges. The hybrid HSE functional with spin–orbit coupling included, in combination with the band edge shifts from G_0W_0 is the only approach that accurately captures both the intrinsic conductivity type of PbTe as function of synthesis conditions as well as the measured charge carrier concentrations, without the need for experimental inputs. Our results reaffirm the critical role of the position of individual band edges in defect calculations, and demonstrate that dopability can be accurately predicted in such challenging narrow band gap materials.
Impact of climate change on the small mammal community of the Yukon boreal forest

Long-term monitoring is critical to determine the stability and sustainability of wildlife populations, and if change has occurred, why. We have followed population density changes in the small mammal community in the boreal forest of the southern Yukon for 46 years with density estimates by live trapping on 3–5 unmanipulated grids in spring and autumn. This community consists of 10 species and was responsible for 9% of the energy flow in the herbivore component of this ecosystem from 1986 to 1996, but this increased to 38% from 2003 to 2014. Small mammals, although small in size, are large in the transfer of energy from plants to predators and decomposers. Four species form the bulk of the biomass. There was a shift in the dominant species from the 1970s to the 2000s, with Myodes rutilus increasing in relative abundance by 22% and Peromyscus maniculatus decreasing by 22%. From 2007 to 2018, Myodes comprised 63% of the catch, Peromyscus 20%, and Microtus species 17%. Possible causes of these changes involve climate change, which is increasing primary production in this boreal forest, and an associated increase in the abundance of 3 rodent predators, marten(Martes americana), ermine(Mustela ermine) and coyotes(Canis latrans). Following and understanding these and potential future changes will require long-term monitoring studies on a large scale to measure metapopulation dynamics. The small mammal community in northern Canada is being affected by climate change and cannot remain stable. Changes will be critically dependent on food–web interactions that are species-specific.
Diet shift in bank voles induced by competition from grey-sided voles?

Grey-sided voles (Myodes rufocanus)and bank voles (Myodes glareolus)co-exist in boreal forests in northern Scandinavia. Previous studies suggest that the 2 species interact interspecifically, the grey-sided vole being the dominant species. We tested the hypothesis that bank voles shift their diet due to competition with the dominant grey-sided vole by studying stable isotope ratios in both species. Muscle samples were taken from voles in patches of old forest occupied by only bank voles and patches of old forest occupied by both grey-sided voles and bank voles. We found that: (i)stable isotope ratios of bank voles differed in areas with and without grey-sided voles; and that (ii)the stable isotope ratios of bank voles were more similar to those of grey-sided voles in areas where grey-sided voles were absent. Our data suggests that grey-sided voles forced bank voles to change their diet due to interspecific competition.
再生障碍性贫血诊断与治疗中国专家共识（2017年版）

为进一步提高我国再生障碍性贫血(AA)的诊治水平,中华医学会血液学分会红细胞疾病(贫血)学组在《再生障碍性贫血诊断治疗专家共识》(2010版)的基础上,参考国外诊治指南及近年相关文献,广泛征求专家建议和意见,重新制订了以下AA诊断与治疗新版中国专家共识。
Implementation of multilayer perceptron (MLP) and radial basis function (RBF) neural networks to predict solution gas-oil ratio of crude oil systems

Exact determination of pressure-volume-temperature (PVT) properties of the reservoir oils is necessary for reservoir calculations, reservoir performance prediction, and the design of optimal production conditions. The objective of this study is to develop intelligent and reliable models based on multilayer perceptron (MLP) and radial basis function (RBF) neural networks for estimating the solution gas–oil ratio as a function of bubble point pressure, reservoir temperature, oil gravity (API), and gas specific gravity. These models were developed and tested using a total of 710 experimental data sets representing the samples of crude oil from various geographical locations around the world. Performance of the developed MLP and RBF models were evaluated and investigated against a number of well-known empirical correlations using statistical and graphical error analyses. The results indicated that the proposed models outperform the considered empirical correlations, providing a strong agreement between predicted and experimental values, However, the developed RBF exhibited higher accuracy and efficiency compared to the proposed MLP model.
Temperature profile estimation: A study on the Boberg and Lantz steam stimulation model

Cyclic steam stimulation (CSS) is widely used for production from heavy oil reservoirs where oil viscosity is manipulated by heat. Many analytical models have been developed to predict the temperature evolution in the reservoir and estimate the oil recovery. However, they often suffer from a number of assumptions which ultimately reduce their efficiency in providing a realistic prediction. In this study, a numerical solution was proposed for two-dimensional heat conduction in heavy oil reservoirs to obtain the temperature evolution during the soaking period. For a better comparison, an industry widely accepted analytical model, knows as the Boberg and Lantz steam stimulation model, together with its modified version later proposed by Bensten and Donohue were considered to examine temperature changes in a synthetic case study. The results obtained indicated that the analytical solutions overestimate the average temperature of the reservoir by 42% after 300 days of injection while the numerical formulation can provide a close prediction. This numerical approach could be a useful tool to estimate the temperature and oil production from heavy oil reservoirs.
Characterization of retinal microvasculature in acute non-arteritic anterior ischemic optic neuropathy using the retinal functional imager: a prospective case series

Background: Non-arteritic anterior ischemic optic neuropathy (NAION) is the most common cause of acute optic neuropathy in patients over 50 years of age, and many affected individuals are left with permanent visual deficits. Despite the frequency of NAION and its often devastating effects on vision, no effective treatment has been established. Further understanding of the acute vascular effects in NAION, using advanced ophthalmic imaging techniques like the retinal function imager, may shed light on potential treatment targets. Methods: Five patients with acute NAION underwent retinal functional imaging within 2 weeks of the onset of their visual symptoms, and at 1 month and 3 months after onset. Average arteriolar and venular blood flow velocities were calculated for each eye at each time point. The Wilcoxon rank sum test was used to compare blood flow velocity results with a normative database. Results: The average arteriolar blood flow velocity in the normative group was 3.8 mm/s, and the average venular blood flow velocity was 3.0 mm/s, versus 4.1 mm/s and 2.7 mm/s, respectively, in the NAION-affected group at presentation. Average arteriolar blood flow increased slightly to 4.2 mm/s one month after the acute NAION event, then decreased to 3.8 mm/s three months after the event. Average venular blood flow velocity was 2.8 mm/s 1 month after the NAION event and 2.7 mm/s 3 months after the event. Differences in blood flow velocity between the NAION-affected and control groups were not statistically significant at any time point; however, there was a trend toward increasing blood flow velocity initially after an NAION, with a decrease over time. Conclusions: This study demonstrates the feasibility of retinal function imaging to quantify macular blood flow velocity in patients with acute NAION. There were no statistically significant differences in blood flow velocity detected between NAION-affected eyes and healthy controls at any of the time points examined; however, there was a trend toward an increase in both arteriolar and venular BFV subacutely, then a decrease in the chronic phase after NAION, which could be suggestive of a mechanism of attempted compensation in the setting of acute ischemia.
Dynamics and Small Signal Stability Analysis of PMSG-based Wind Farm with an MMC-HVDC System

The permanent magnet synchronous generator (PMSG)-based wind farm with a modular multilevel converter (MMC) based HVDC system exhibits various oscillations and can experience dynamic instability due to the interactions between different controllers of the wind farm and MMC stations, which have not been properly examined in the existing literatures. This paper presents a dynamic modeling approach for small signal stability analysis of PMSG-based wind farms with a MMCHVDC system. The small signal model of the study system is validated by the comprehensive electromagnetic transient (EMT) simulations in PSCAD/EMTDC. Then the eigenvalue approach and participation factors analysis are utilized to comprehensively evaluate the impact of different controllers, system’s parameters and the circulating current suppressing controller (CCSC) on the small signal stability of the entire system. From eigenvalue analysis, it is revealed that as the output active power of the wind farm increases within the rated range, the overall system will exhibit a sub-synchronous oscillation (SSO) instability mode, an extremely weak damping mode, and a low frequency oscillation instability mode. From participation factors analysis, it is observed that the SSO mode and weak damping mode are primarily related to the internal dynamics of the MMC, which can be suppressed or improved by CCSC. It is determined that the low frequency oscillation mode is primarily caused by the interactions between the phase locked loop (PLL) control of the wind farm and the voltage and frequency (V-F) control of the MMC station. The analysis also depicts that the larger proportional gain value of the V-F control of the MMC station and smaller PLL bandwidth of the wind farm can enhance the small signal stability of the entire system.
Fast Identification of Symmetrical or Asymmetrical Faults During Power Swings with Dual Use Line Relays

Increasing power demand, penetration of renewables, and limitations of necessary grid expansion are proffering new challenges to existing power system protection and control strategies. However, with the advancement in intelligent electronic devices and relaying technology, fast, accurate and reliable protection schemes can be developed for smart power systems. In this paper, a new protection scheme based on admittance and power change has been proposed with dual-use line relays to detect symmetrical/asymmetrical faults in power systems. A large number of fault environments have been simulated by varying fault distances from relay location, fault resistance, and power angle in single machine infinite bus and WSCC 9-bus systems. Some crucial decisive fault scenarios e.g. close in/far end faults, faults in series compensated line, faults during asymmetrical swings, switching ON/OFF large loads, single and multi-modal swings have also been verified for the proposed index. In this paper, for the first time, detection of faults during power swings have been examined and verified in the presence of wind farms. The simulation results show the proficiency of the proposed algorithm for detecting faults in the presence or absence of power swings.
Deep Reinforcement Learning for Power System Applications: An Overview

Due to increasing complexity, uncertainty and data dimensions in power systems, conventional methods often meet bottlenecks when attempting to solve decision and control problems. Therefore, data-driven methods toward solving such problems are being extensively studied. Deep reinforcement learning (DRL) is one of these data-driven methods and is regarded as real artificial intelligence (AI). DRL is a combination of deep learning (DL) and reinforcement learning (RL). This field of research has been applied to solve a wide range of complex sequential decision-making problems, including those in power systems. This paper firstly reviews the basic ideas, models, algorithms and techniques of DRL. Applications in power systems such as energy management, demand response, electricity market, operational control, and others are then considered. In addition, recent advances in DRL including the combination of RL with other classical methods, and the prospect and challenges of applications in power systems are also discussed.
Overview of Energy Storage in Renewable Energy Power Fluctuation Mitigation

The integration of renewable energy, such as PV and wind power, has exerted great impacts on the power system with its rapid development. If the corresponding energy storage system is configured, the power system could be able to hold a higher proportion of renewable energy. Focusing on energy storage application for the output fluctuation mitigation of renewable energy, this paper first analyses the reason for renewable energy power fluctuation mitigation from the four aspects of frequency, unit ramp, low frequency oscillation and cascading failure. In addition, the fluctuation rate standard of grid-connected renewable energy, the energy storage type and the mitigation topology are introduced. Then a summary and analysis on mitigation strategy and hybrid energy storage allocation strategy are presented. Finally, the demonstration application and development trend of energy storage are analyzed to provide reference for the promotion of energy storage in renewable energy.
Day-ahead Optimization Schedule for Gas-electric Integrated Energy System Based on Second-order Cone Programming

This paper proposes an optimal day-ahead optimization schedule for gas-electric integrated energy system (IES) considering the bi-directional energy flow. The hourly topology of electric power system (EPS), natural gas system (NGS), energy hubs (EH) integrated power to gas (P2G) unit, are modeled to minimize the day-ahead operation cost of IES. Then, a second-order cone programming (SOCP) method is utilized to solve the optimization problem, which is actually a mixed integer nonconvex and nonlinear programming issue. Besides, cutting planes are added to ensure the exactness of the global optimal solution. Finally, simulation results demonstrate that the proposed optimization schedule can provide a safe, effective and economical day-ahead scheduling scheme for gas-electric IES.