bluuebunny/crossref_metadata_2025 huggingface dataset:
Prediction of Vortex-Induced Vibration Response of Open Bridge Girder Based on Machine Learning Method
Authors: Ma Zhen-Xing , Li Jia-Wu , Wang Feng , Cheng Ling-Xiang , Zhao Guo-Hui , Qiao Xiao-Ru
Published: April 2023

The [Formula: see text]-shaped open section girder is a very common section, which has been widely used in the construction of modern bridges. However, compared with a streamlined box girder, it is easy to cause vortex-induced vibration (VIV) in bridges due to its bluff section shape and poor aerodynamic stability.

In this paper, a typical open section with a height–width ratio of 10:1 is taken as the research object. Through wind tunnel tests and numerical simulation technology, the time-history data of VIV of the [Formula: see text]-shaped section are obtained. By selecting three different neural network models to establish the relationship between external parameters (wind attack angle, wind speed, turbulence) and structural response parameters (the onset wind speed of VIV, the length of the lock-in interval). After comparing different machine learning methods, the most suitable machine learning model is selected to predict the VIV response characteristics of the main girder. The research results show that the typical open section has a serious VIV phenomenon. The BP neural network model has the best performance in predicting the VIV performance of the open section in terms of calculation speed, prediction accuracy and solving nonlinear adaptability. At the same time, it is found that different characteristic parameters of the incoming wind field have different influences on the prediction results of the VIV response. Among them, the wind attack angle is the key parameter that affects the onset wind speed of VIV, but the turbulence intensity has a greater impact on the maximum amplitude of VIV. At the same time, the optimized BP model can predict the characteristic parameters of VIV response under unknown wind fields. This paper provides a new idea to study the effect of different incoming flow parameters on the performance of section VIV and further improves people’s understanding of VIV system.
Computation of depth of factor rings of C(X)
Authors: Hesari A. A. , Salehi A. R.
Published: April 2023

It is known that the depth of every factor ring of [Formula: see text] module an ideal is at most 1. In this paper, we examine conditions under which the depth of factor rings of [Formula: see text] module closed ideals are either 0 or 1. Particularly, we show that the depth of factor ring [Formula: see text], [Formula: see text], is 0 (or equivalently this ring is classical i.e. its every element is unit or zerodivisor) if and only if [Formula: see text] is an almost [Formula: see text]-space completely separated from every zero-set disjoint from it. Using this, it has been confirmed that [Formula: see text] modulo the smallest [Formula: see text]-ideal containing [Formula: see text] is classical if and only if [Formula: see text] is an almost [Formula: see text]-space completely separated from every zero-set disjoint from it. Also, it has been verified that [Formula: see text] is a [Formula: see text]-space if and only if for every ideal [Formula: see text], the factor ring [Formula: see text] has depth zero. Finally, we present a counterexample to a conjecture about the depth of subrings of [Formula: see text] in the literature.
Dynamical analysis and chaos control of a fractional-order Leslie-type predator–prey model with Caputo derivative
Authors: Işık Seval , Kangalgil Figen
Published: April 2023

In this paper, the dynamical behaviors of a discrete-time fractional-order population model are considered. The stability analysis and the topological classification of the model at the fixed point have been investigated. It is shown that the model undergoes flip and Neimark–Sacker bifurcations around the co-existence fixed point by using the bifurcation and the normal form theory. These bifurcations lead to chaos when the parameter changes at critical point. In order to control chaotic behavior in the model result from Neimark–Sacker bifurcation, the OGY feedback method has been used. Furthermore, some numerical simulations, including bifurcation diagrams, phase portraits and maximum Lyapunov exponents of the presented model are plotted to support the correctness of the analytical results. The positive Lyapunov exponents demonstrate that chaotic behavior exists in the considered model.
Return of the NPLs to the Bright Side: Which Unlikely to Pay Firms are More Likely to Pay?
Authors: Affinito Massimiliano , Meucci Giorgio
Published: April 2023

Bank loans are divided into performing and non-performing loans (NPLs). NPLs are in turn divided into categories characterized by different degrees of difficulty of the debtor and level of risk for the creditor bank. Unlikely to pay loans (UTPs) are NPLs that have a non-zero probability of returning to the performing status. This paper analyzes at the firm and bank level the entire pool of UTPs vis-à-vis firms (UTP firms) in Italy from 2005 to 2019 to detect the characteristics of UTP firms that are more likely to return to the performing state. So far, the literature focused only on status changes from performing to NPLs. To our knowledge, this is the first paper that reverses the perspective and examines the drivers of return to the performing state. The paper shows that the factors most closely related to the new upgrade are — negatively — firm size and absolute value of debts, and — positively — capital and liquidity endowments. Results show that the soundness of lending banks increases the likelihood that firms return to the performing state.
Awareness, Intention, (In)Action: Individuals’ Reactions to Data Breaches
Authors: Mayer Peter , Zou Yixin , Lowens Byron M. , Dyer Hunter A. , Le Khue , Schaub Florian , Aviv Adam J.
Published: April 2023

Data breaches are prevalent. We provide novel insights into individuals’ awareness, perception, and responses to breaches that affect them through two online surveys: a main survey (n= 413) in which we presented participants with up to three breaches that affected them, and a follow-up survey (n= 108) in which we investigated whether the main study participants followed through with their intentions to act. Overall, 73% of participants were affected by at least one breach, but participants were unaware of 74% of breaches affecting them. Although some reported intention to take action, most participants believed the breach would not impact them. We also found a sizable intention-behavior gap. Participants did not follow through with their intention when they were apathetic about breaches, considered potential costs, forgot, or felt resigned about taking action. Our findings suggest that breached organizations should be held accountable for more proactively informing and protecting affected consumers.
Neurotechnology for Pain
Authors: Fisher Lee E. , Lempka Scott F.
Published: April 2023

Neurotechnologies for treating pain rely on electrical stimulation of the central or peripheral nervous system to disrupt or block pain signaling and have been commercialized to treat a variety of pain conditions. While their adoption is accelerating, neurotechnologies are still frequently viewed as a last resort, after many other treatment options have been explored. We review the pain conditions commonly treated with electrical stimulation, as well as the specific neurotechnologies used for treating those conditions. We identify barriers to adoption, including a limited understanding of mechanisms of action, inconsistent efficacy across patients, and challenges related to selectivity of stimulation and off-target side effects. We describe design improvements that have recently been implemented, as well as some cutting-edge technologies that may address the limitations of existing neurotechnologies. Addressing these challenges will accelerate adoption and change neurotechnologies from last-line to first-line treatments for people living with chronic pain.
RNA Crossing Membranes: Systems and Mechanisms Contextualizing Extracellular RNA and Cell Surface GlycoRNAs
Authors: Chai Peiyuan , Lebedenko Charlotta G. , Flynn Ryan A.
Published: April 2023

The subcellular localization of a biopolymer often informs its function. RNA is traditionally confined to the cytosolic and nuclear spaces, where it plays critical and conserved roles across nearly all biochemical processes. Our recent observation of cell surface glycoRNAs may further explain the extracellular role of RNA. While cellular membranes are efficient gatekeepers of charged polymers such as RNAs, a large body of research has demonstrated the accumulation of specific RNA species outside of the cell, termed extracellular RNAs (exRNAs). Across various species and forms of life, protein pores have evolved to transport RNA across membranes, thus providing a mechanistic path for exRNAs to achieve their extracellular topology. Here, we review types of exRNAs and the pores capable of RNA transport to provide a logical and testable path toward understanding the biogenesis and regulation of cell surface glycoRNAs.
The Microbiology of Biological Soil Crusts
Authors: Garcia-Pichel Ferran
Published: April 2023

Biological soil crusts are thin, inconspicuous communities along the soil atmosphere ecotone that, until recently, were unrecognized by ecologists and even more so by microbiologists. In its broadest meaning, the term biological soil crust (or biocrust) encompasses a variety of communities that develop on soil surfaces and are powered by photosynthetic primary producers other than higher plants: cyanobacteria, microalgae, and cryptogams like lichens and mosses. Arid land biocrusts are the most studied, but biocrusts also exist in other settings where plant development is constrained. The minimal requirement is that light impinge directly on the soil; this is impeded by the accumulation of plant litter where plants abound. Since scientists started paying attention, much has been learned about their microbial communities, their composition, ecological extent, and biogeochemical roles, about how they alter the physical behavior of soils, and even how they inform an understanding of early life on land. This has opened new avenues for ecological restoration and agriculture.
Optimal UPFC Placement for Voltage Stability Enhancement
Authors: Pandian Arun Nambi , Palanivelu Aravindhababu
Published: April 2023

The Unified Power Flow Controller is a versatile and important device for improving the operational efficiency of power systems in the flexible AC transmission systems family. It finds applications in improving voltage stability in addition to provide a better voltage profile and reducing transmission loss. This paper presents a Chemical Reaction Inspired Optimization based method for placement of unified power flow controllers with the objective of raising the voltage stability. Most of the existing methods place all the given unified power flow controllers without analysing whether each of the given unified power flow controllers is actually needed to improve voltage stability or other selected performances. The proposed method tries to place only the essential unified power flow controllers from the allocated number of devices, besides providing optimal line locations and unified power flow controller parameters. It also includes the results of the proposed method for three standard test systems and compares them with existing methods to depict the dominance of the proposed method.
Green Synthesis of Calcium/Iron-Layered Double Hydroxides-Sodium Alginate Nanoadsorbent as Reactive Barrier for Antibiotic Amoxicillin Removal from Groundwater
Authors: Abed Marwa F. , Faisal Ayad A. H.
Published: April 2023

This work uses a new nanoadsorbent after chemically synthesis from chicken eggshell wastes for removing amoxicillin (AMX) from aqueous solution. This removal was examined as a time function, initial concentration of AMX, pH, agitation speed, and adsorbent dosage. The study achieved the optimum time for equilibration in (90) min, at [Formula: see text] with an adsorbent dosage of 1.2 g. We applied many kinetic models to the sorption kinetic data where the pseudo-second-order model ([Formula: see text]) was used to interpret the gained data at a rate constant K2 of (0.0077) g/(mg. min) at 200 rpm. Moreover, the adsorption calculated amount reached the experimentally required value and isotherm data best fitted the Langmuir model with [Formula: see text] (≥0.9486) than the Freundlich model. The intraparticle diffusion model revealed a diffusion dependent process. The different functional sets on the calcium/iron-surface as a layered double hydroxide (Ca/Fe)-LDH were important in sorpting the selected antibiotic. Forming (Ca/Fe)-LDH nanoparticles in the manufactured beads interacted with polluted water confirming that the nanoparticles own the prospective for acting as a latent sorbent to remove contaminants from aquatic media.
Collective Dynamical Behaviors of Nonlocally Coupled Brockett Oscillators
Authors: Ramadoss Janarthan , Durairaj Premraj , Rajagopal Karthikeyan , Akgul Akif
Published: April 2023

In this study, we consider a network of nonlocally coupled Brockett oscillators (BOs) with attractive and repulsive (AR) couplings to illustrate the existence of diverse collective dynamical behaviors, whereas previous studies solely concentrated on synchronization. In the absence of coupling, the individual BO oscillator shows stable periodic oscillations (POs) or stable steady state (SS) depending on the critical values of the parameters. We first begin by examining the collective dynamics by setting the critical value of the parameters at the active (PO) region. A diverge collective dynamical states are manifested for a fixed nonlocal coupling range with rising coupling magnitude. Notably, the lower coupling strength exhibits two distinct dynamical patterns at lower and higher transients. At lesser transients, for example, transient dynamics of desynchronization, chimera, and traveling wave states are observed. At larger time periods, the transient dynamics disappear with the emergence of a synchronized state. Increasing the coupling strength results in a unique state of traveling wave or synchronized state for smaller and larger time periods depending on the coupling strength. Increasing the coupling strength further gives rise to clustering behaviors. Importantly, the considered system attains cluster oscillation death (COD) through a cluster oscillatory state (COS). Finally, there exists a chimera death at a larger coupling strength. The observed dynamical transitions are further demonstrated through the two‐parameter analysis by setting different critical thresholds.
Local Binary Convolutional Neural Networks' Long Short-Term Memory Model for Human Embryos' Anomaly Detection
Authors: Einy Sajad , Sen Esra , Saygin Hasan , Hivehchi Hemrah , Dorostkar Navaei Yahya
Published: April 2023

Accurate selection of embryos with the maximum implementation condition is a necessary step to increase the effectiveness of fertility treatment in in vitro fertilization (IVF). The deep learning algorithms presented high potential for monitoring and visualizing embryo features such as cell numbers and their morphological development in time series manner. Due to the ability of the computer vision and deep learning algorithms, this paper aimed to present a novel deep learning approach to distinguish simultaneous abnormality of embryos in time-lapse systems for detecting live and non-live births in IVF. The approach is composed of local binary convolutional neural network (LBCNN) and long short-term memory (LSTM). The LBCNN improved accuracy of classification by employing deep and local feature sets with lower number of learnable parameters in comparison with a standard convolutional layer. Moreover, LSTM network is employed to analyze temporal information of time-lapse embryos. The results indicate that the proposed approach achieves significant results in ROC analysis (0.98) in 5 days of monitoring compared to state-of-the-art models. In addition, the approach showed compatible results in early diagnosis of abnormality detection (72 hours) with 82.8% accuracy of classification compared to the pretrained well-known convolutional neural network (CNN) models and baseline CNN.
Depressive Symptoms are Associated with More Negative Global Metacognitive Biases in Combat Veterans, and Biases Covary with Symptom Changes over Time
Authors: Agnoli Sam , Zuberer Agnieszka , Nanni-Zepeda Melanni , McGlinchey Regina E. , Milberg William P. , Esterman Michael , DeGutis Joseph
Published: April 2023

Metacognitive awareness, insight into one’s abilities, is thought to be disrupted in depression and posttraumatic stress disorder (PTSD), with more negative metacognitive biases and reduced awareness, respectively. However, studies have rarely examined global aspects of metacognitive awareness in depression and PTSD, instead using task-specific measures. In 467 trauma-exposed post-9/11 veterans, we administered assessments of PTSD and depression, self-report and objective measures of cognitive functioning (neuropsychological battery of memory, attention, and executive function measures), and self-report and objective measures of general health (index of five cardiometabolic factors). We used self-report/objective correlations to measure metacognitive sensitivity and 'self-report minus objective' scores to measure bias. We also examined associations between changes in metacognitive awareness and changes in PTSD and depression over time. Metacognitive sensitivity was comparable between individuals with and without PTSD and depression. However, metacognitive bias was significantly more negative in those with greater depressive symptoms (i.e., underconfidence) across cognition and health, independent of PTSD symptoms. Notably, metacognitive bias changes covaried with depressive and PTSD symptom changes two years later. This shows that, in trauma-exposed veterans, negative metacognitive biases are specifically related to depressive symptoms and these biases may be relatively domain general. Further, our longitudinal results suggest that, rather than being a stable trait, metacognitive biases change with PTSD/depressive symptoms over time.
Research on Credit Risk Prediction under Unbalanced Dataset Based on Ensemble Learning
Authors: Chen Hailong , Yang Chang , Du Mei , Zhang Yingyu
Published: April 2023

Aiming at the problem of high‐dimensional features and data imbalance in credit risk assessment that affect model prediction results, a credit risk prediction method based on integrated learning is proposed from three levels of features, data and algorithms. First, a hybrid filter and Random Forest feature selection method is used to select features. This method uses the improved Relief algorithm to initially select features, then combines the maximum information coefficient to eliminate redundant features, and uses the Random Forest algorithm to further reduce the feature dimension. Second, on the basis of the Borderline‐SMOTE method, an adaptive idea is introduced to generate a different number of new samples for each minority sample at the boundary, and a new interpolation method is used to make the new sample distribution more reasonable, so as to reduce the sample imbalance. Finally, the Focal Loss is used to improve the loss function of LightGBM, and the sample weight is adjusted through the parameters α and γ in the Focal Loss function so that the model pays more attention to minority samples and difficult‐to‐classify samples, and improves the accuracy of model classification. And use the improved algorithm as the base classifier and then use AdaBoost and random subspace methods to integrate to establish a credit risk prediction model. Through comparative experiments with other methods, the results show that this method effectively improves the G‐mean value and the AUC value and has a better default prediction effect.
Influence of Fuel Oxygenation on Regulated Pollutants and Unregulated Aromatic Compounds with Biodiesel and n-Pentanol Blends
Authors: Yilmaz Nadir , Vigil Francisco M. , Atmanli Alpaslan , Donaldson Burl
Published: April 2023

It is very important to determine the polycyclic aromatic hydrocarbon (PAH) emissions caused by the use of renewable fuels in diesel engines and to know the possible damages. This study investigates the emissions (regulated and unregulated) of biodiesel/n-pentanol mixtures, which are free of aromatic content, with emphasis on PAH formation and an examination of toxicity to public health and the environment. Engine failures caused by wetstacking are also discussed. Biodiesel/n-pentanol fuel mixtures with alcohol concentrations of 5%, 20%, and 35% by volume (v/v) served as test fuels in a compression ignition engine. A five-gas analyzer was used to measure hydrocarbon (HC), carbon monoxide (CO), and nitrogen oxide (NOx) emissions. Polycyclic aromatic hydrocarbons were detected and measured using gas chromatography-mass spectrometry (GC-MS). Against the baseline diesel fuel, the biodiesel/n-pentanol fuel blends and neat biodiesel reduced NOx emissions and produced significantly fewer PAHs and toxicity, confirming the significance of the aromatic content of the fuel. Biodiesel reduced total PAHs by 48.02% and the addition of 5% n-pentanol to biodiesel further decreased total PAHs by 21.26%. The total toxicity (BaPeq (benzo[a]pyrene equivalent)) as a result of biodiesel was 83.49% less than diesel. The addition of n-pentanol to biodiesel further reduced toxicity by 59.15%, 57.89%, and 48.33% for BPen5, BPen20, and BPen35 blends, respectively. In addition, n-pentanol was shown to be effective for reducing total PAH emissions, as well as heavier PAHs, which have greater carcinogenicity and pose a greater likelihood of engine damage from wetstacking when running in low-load conditions at cold temperatures.
Hamiltonicity in Directed Toeplitz Graphs with

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Authors: Malik Shabnam
Published: April 2023

A directed Toeplitz graph

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is a directed graph whose adjacency matrix is a Toeplitz matrix. In this paper, we investigate the Hamiltonicity in directed Toeplitz graphs

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A Coupled Model for Dam Foundation Seepage Behavior Monitoring and Forecasting Based on Variational Mode Decomposition and Improved Temporal Convolutional Network
Authors: Zhu Yantao , Zhang Zhiduan , Gu Chongshi , Li Yangtao , Zhang Kang , Xie Mingxia
Published: April 2023

Grasping the change behavior of dam foundation seepage pressure is of great significance for ensuring the safety of concrete dams. Because of the environmental complexity of the dam location, the prototypical seepage pressure data are easy to be contaminated by noise, which brings challenges to accurate prediction. Traditional denoising methods will lose the detailed characteristics of the objects, resulting in prediction models with limited flexibility and prediction accuracy. To address these problems, the prototypical data with noise are denoised using the variational mode decomposition (VMD)-wavelet packet denoising method. Then, an improved temporal convolutional network (ITCN) model is built for dam foundation seepage pressure data prediction. A hysteresis experiment is carried out to optimize the model structure by correlating the receptive field size of the ITCN model with the hysteresis of the dam foundation seepage pressure. Finally, the optimal ITCN dam foundation seepage pressure prediction model of each measurement point is obtained after the training. Three state-of-the-art methods in dam seepage monitoring are used as benchmark methods to compare the prediction performance of the proposed method. Four evaluation indicators are introduced to quantitatively evaluate and compare the prediction performance of the proposed method. The experimental results prove that the proposed method achieves high prediction accuracy flexibility. The indicator values of the ITCN model are only 50%–90% of those of LSTM and RNN models and 15%–40% of those of the stepwise regression model, and the values are all small.
User Satisfaction of Using Electronic Medical Record System and Its Associated Factors among Healthcare Professionals in Ethiopia: A Cross‐Sectional Study
Authors: Dubale Abiy Tasew , Mengestie Nebyu Demeke , Tilahun Binyam , Walle Agmasie Damtew
Published: April 2023

Background. Electronic medical record (EMR) systems have become essential for the proper management of patients’ information. Electronic medical record systems are on the rise in developing countries due to the need to ensure improved quality of healthcare. However, EMR systems can be ignored, if users are not satisfied with the implemented system. User dissatisfaction has been associated with the failure of EMR systems as a primary factor. There is also limited research done in the Ethiopian context on EMR user satisfaction at private hospitals. This study is aimed at assessing user satisfaction with electronic medical records and associated factors among health professionals working at private hospitals in Addis Ababa. Methods. Institution‐based cross‐sectional quantitative study was conducted among health professionals working at private hospitals in Addis Ababa, from March to April 2021. A self‐administered questionnaire was used to collect the data. EpiData version 4.6 and Stata version 25 were used for data entry and analysis, respectively. Descriptive analyses were computed for the study variables. Bivariable and multivariable logistic regression analyses were carried out to assess the significance of independent variables on dependent variables. Results. A total of 403 (95.33% response rate) participants completed all the questionnaires. More than half of 214 (53.10%) of the participants were satisfied with the EMR system. Factors associated with user satisfaction with electronic medical records were good computer literacy (AOR = 2.92, 95% CI: [1.16‐7.37]), perceived information quality (AOR = 3.54, 95% CI: [1.55‐8.11]), perceived service quality (AOR = 3.15, 95% CI: [1.58‐6.28]), perceived system quality (AOR = 3.05, 95% CI: [1.32‐7.05]), EMR training (AOR = 4.00, 95% CI: [1.76‐9.03]), computer access (AOR = 3.17, 95% CI: [1.19‐8.46]), and HMIS training (AOR = 2.05, 95% CI: [1.22‐6.71]). Conclusions. In this study, health professionals’ EMR satisfaction was moderate. The result showed that EMR training, computer literacy, computer access, perceived system quality, information quality, service quality, and HMIS training were associated with user satisfaction. Improving computer‐related training, system quality, information quality, and service quality is an important intervention to improve the healthcare professional’s satisfaction towards using electronic health record systems in Ethiopia.
The Correlation between Traditional Chinese Medicine Constitution and Hyperuricemia and Gout: A Systematic Review and Meta‐Analysis
Authors: Jiang Zihao , Chen Jieyu , You Yanting , Ji Shuai , Chen Liqian , He Qiuxing , Liu Yanyan , Sun Xiaomin , Zhou Lin , Zhao Xiaoshan
Published: April 2023

Objective. To investigate the correlation between the constitution of traditional Chinese medicine (TCM) and hyperuricemia (HUA) and gout. Method. Databases including China National Knowledge Infrastructure (CNKI), WanFang Data, China Science and Technology Journal Database (VIP), China Biology Medicine Disc (CBMdisc), PubMed, The Cochrane Library, Web of Science, and Excerpta Medical Database (Embase) were searched to collect observational studies about TCM constitution in HUA and gout from inception to November 21, 2021. The distribution of TCM constitution types in HUA and gout patients was presented by proportion, while the correlation was presented by odds ratio (OR) and 95% CI. Meta‐analysis was performed using StataCorp Stata (STATA) version 16.0 software. Results. Twenty‐one cross‐sectional studies and 10 case‐control studies involving 38028 samples were included, among which 27526 patients were diagnosed with HUA and 2048 patients with gout. Phlegm‐dampness constitution (PDC), damp‐heat constitution (DHC), and qi‐deficiency constitution (QDC) are the most common types, accounting for 24% (20%–27%), 22% (16%–27%), and 15% (12%–18%), respectively, in HUA patients, while DHC, PDC, and blood stasis constitution (BSC) accounted for 28% (18%–39%), 23% (17%–29%), and 11% (8%–15%), respectively, in gout patients. PDC and DHC were the main constitution types in patients with HUA or gout in south China, east China, north China, southwest China, northwest China, and northeast China. There was no difference in the distribution of PDC and QDC in male or female patients with HUA, while males with DHC in HUA were more common than females. The proportion of PDC or DHC among HUA patients was 1.93 times and 2.14 times higher than that in the general population (OR and 95% CI: 1.93 (1.27, 2.93), 2.14 (1.47, 3.13)), while the proportions of PDC, DHC, and BSC were 3.59 times, 4.85 times, and 4.35 times higher than that of the general groups (OR and 95% CI: 3.59 (1.65, 7.80), 4.85 (1.62, 14.57), and 4.35(2.33, 8.11)). Conclusion. PDC, DHC, and QDC are the main constitution types of patients with HUA, while PDC and QDC may be the risk factors for HUA. DHC, PDC, and BSC are the main constitution types of patients with gout, and they may be the risk factors for gout. In clinical and scientific research, more attention should be paid to the relationship between the above‐mentioned TCM constitution in HUA or gout. Nevertheless, because the quality of the included observational studies is low, more prospective cohort studies related to TCM constitution and HUA or gout can be carried out to verify the causality between TCM constitution and HUA or gout.
Network Model with Scale-Free, High Clustering Coefficients, and Small-World Properties
Authors: Yan Chuankui
Published: April 2023

Networks are prevalent in real life, and the study of network evolution models is very important for understanding the nature and laws of real networks. The distribution of the initial degree of nodes in existing classical models is constant or uniform. The model we proposed shows binomial distribution, and it is consistent with real network data. The theoretical analysis shows that the proposed model is scale-free at different probability values and its clustering coefficients are adjustable, and the Barabasi-Albert model is a special case of

p
=
0

in our model. In addition, the analytical results of the clustering coefficients can be estimated using mean-field theory. The mean clustering coefficients calculated from the simulated data and the analytical results tend to be stable. The model also exhibits small-world characteristics and has good reproducibility for short distances of real networks. Our model combines three network characteristics, scale-free, high clustering coefficients, and small-world characteristics, which is a significant improvement over traditional models with only a single or two characteristics. The theoretical analysis procedure can be used as a theoretical reference for various network models to study the estimation of clustering coefficients. The existence of stable equilibrium points of the model explains the controversy of whether scale-free is universal or not, and this explanation provides a new way of thinking to understand the problem.
Application of Photovoltaic Systems in Field Observation and Research Stations: Research on the Relationship between Power Generation Scale and Electricity Consumption to Improve Photovoltaic Application in Field Observation Stations
Authors: Yao Jianan , Zhu Junfeng , Wang Binbin , Niu Junkui , Liu Wenbing , Chen Long , Song Yifan
Published: April 2023

Most field scientific observation and research stations are located at the end of power grids which are usually not extended to such areas. Consequently, the power supply of equipment in field observation stations cannot be guaranteed. Meanwhile, regions with poor ecosystem stability are relatively sensitive to environmental changes and thus prone to degradation and succession due to external interference. In this paper, the photovoltaic (PV) power generation system of a grassland ecohydrological field scientific observation and research station was taken as the research object. Two kinds of distributed PV power generation systems were simulated and analyzed by use of PVsyst software. The total power of laboratory equipment, PV power generation efficiency, and system cost of the field observation station were calculated and analyzed. The design scheme and scale of PV power generation systems suitable for field observation stations were determined. Finally, a PV power generation test system was set up, and PV power generation data were sorted out. The feasibility of the design scheme of PV power generation systems was verified by analyzing the relationship between the simulated and actual power generation of systems and that between the daily energy use proportions of field observation stations. Besides, the environmental benefits of PV systems were analyzed, and their amount of energy saving and emission reduction was calculated. This study can solve the issue of the low power supply guarantee rate of field observation stations, provide a design basis and beneficial reference for the construction of environment-friendly field laboratory stations, and realize green energy saving and the sustainable use of energy while protecting the ecosystem from being destroyed.
Precedence of Bone Loss Accompanied with Changes in Body Composition and Body Fat Distribution in Patients with Type 2 Diabetes Mellitus
Authors: Zheng Biao , Zheng Yuxin , Zhang Yongze , Huang Lingning , Shen Ximei , Zhao Fengying , Yan Sunjie
Published: April 2023

Background and Objective. Diabetes and osteoporosis are common diseases in elderly people, which are often accompanied by changes in body weight during treatment. No unified conclusion has been reached on the correlation between body weight and osteoporosis yet. This study is aimed at analyzing the correlation between body composition and bone mineral density (BMD) in patients with type 2 diabetes mellitus (T2DM). Methods. A total of 596 patients with T2DM, including 308 male and 288 female patients, were included in the follow-up study; the median follow-up time was 2.17 years. We calculated the difference between the endpoint and the baseline of each body composition index and the annual rate. The research participants were divided into the increased body mass index (BMI) group, stable BMI group, and decreased BMI group. Some confounding factors were adjusted, such as BMI, fat mass index (FMI), muscle mass index (MMI), muscle/fat mass ratio (M/F), trunk fat mass index (TFMI), appendicular skeletal muscle mass index (ASMI), and appendicular skeletal muscle mass/trunk fat mass ratio (A/T). Results. The linear analysis showed that ΔFMI and ΔTFMI were negatively correlated with the change in femoral neck BMD (ΔFNBMD) and ΔMMI, ΔASMI, ΔM/F, and ΔA/T were positively correlated with ΔFNBMD. The risk of FNBMD reduction in patients with increased BMI was 56.0% lower than that in patients with decreased BMI; also, the risk in patients with stable M/F was 57.7% lower than that in patients with decreased M/F. The risk in the A/T increase group was 62.9% lower than that in the A/T decrease group. Conclusions. A reasonable muscle/fat ratio is still beneficial to maintaining bone mass. Maintaining a certain BMI value is conducive to maintaining FNBMD. Simultaneously, increasing the proportion of muscle mass and reducing fat accumulation can also prevent FNBMD loss.
Low Plasma Levels of Hyaluronic Acid Might Rule Out Sinusoidal Obstruction Syndrome after Hematopoietic Stem Cell Transplantation
Authors: De Ramón Ortiz Carmen , Justo Sanz Raul , Beauverd Yan , Humala Karem , López de la Guia Ana , De Paz Raquel , Gasior Mercedes , Gómez Prieto Pilar , Fabra Urdiola Marta , Canales Albendea Miguel , Butta Nora , Jiménez Yuste Victor
Published: April 2023

Background. Sinusoidal obstructive syndrome (SOS) is a potentially fatal complication secondary to hematopoietic stem cell transplant (HSCT) conditioning. Endothelial damage plasma biomarkers such as plasminogen activator inhibitor-1 (PAI-1), hyaluronic acid (HA), and vascular adhesion molecule-1 (VCAM1) represent potential diagnostic tools for SOS. Methods. We prospectively collected serial citrated blood samples (baseline, day 0, day 7, and day 14) in all adult patients undergoing HSCT at La Paz Hospital, Madrid. Samples were later analyzed by ELISA (enzyme-linked immunosorbent assay) for HA, VCAM1, and PAI-1 concentrations. Results. During sixteen months, we prospectively recruited 47 patients. Seven patients (14%) were diagnosed with SOS according to the EBMT criteria for SOS/VOD diagnosis and received treatment with defibrotide. Our study showed a statistically significant elevation of HA on day 7 in SOS patients, preceding clinical SOS diagnosis, with a sensitivity of 100%. Furthermore, we observed a significant increase of HA and VCAM1 levels on day 14. Regarding risk factors, we observed a statistically significant association between SOS diagnosis and the fact that patients received 3 or more previous lines of treatment before HSCT. Conclusions. The early significant increase in HA levels observed opens the door to a noninvasive peripheral blood test which could have the potential to improve diagnosis and facilitate prophylactic and therapeutic management of SOS before clinical/histological damage is established.
Supplementary Table S1 from Single-Cell Spatial Analysis Identifies Regulators of Brain Tumor–Initiating Cells
Authors: Mirzaei Reza , D'Mello Charlotte , Liu Marina , Nikolic Ana , Kumar Mehul , Visser Frank , Bose Pinaki , Gallo Marco , Yong V. Wee
Published: April 2023

Characterization of patients whose resected tissues were used for confocal microscopy.
Supplementary Fig. S9 from Single-Cell Spatial Analysis Identifies Regulators of Brain Tumor–Initiating Cells
Authors: Mirzaei Reza , D'Mello Charlotte , Liu Marina , Nikolic Ana , Kumar Mehul , Visser Frank , Bose Pinaki , Gallo Marco , Yong V. Wee
Published: April 2023

Additional analysis LRP6 and the Wnt/β-catenin pathway activation in BTICs.
Supplementary Fig. S4 from Single-Cell Spatial Analysis Identifies Regulators of Brain Tumor–Initiating Cells
Authors: Mirzaei Reza , D'Mello Charlotte , Liu Marina , Nikolic Ana , Kumar Mehul , Visser Frank , Bose Pinaki , Gallo Marco , Yong V. Wee
Published: April 2023

Additional analysis showing clusters of scRNA-seq analysis with more stemness profiles.
Supplementary Tables & Figures from Preclinical Evaluation of ON203, A Novel Bioengineered mAb Targeting Oxidized Macrophage Migration Inhibitory Factor as an Anticancer Therapeutic
Authors: Rossmueller Gregor , Mirkina Irina , Maurer Barbara , Hoeld Verena , Mayer Julia , Thiele Michael , Kerschbaumer Randolf J. , Schinagl Alexander
Published: April 2023

Includes Supplementary Tables S1-S3 and Supplementary Figures S1-S6
Supplemental Table 2 from Stressful Life Events, Social Support, and Incident Breast Cancer by Estrogen Receptor Status
Authors: Lawrence Wayne R. , McDonald Jasmine A. , Williams Faustine , Shiels Meredith S. , Freedman Neal D. , Lin Ziqiang , Magnani Jared W.
Published: April 2023

Supplemental Table 2: Presents the hazard ratios for the association between Stressful Life Events and incident breast cancer by participant characteristics and estrogen receptor status.
Data from Opportunities for Achieving the Cancer Moonshot Goal of a 50% Reduction in Cancer Mortality by 2047
Authors: Shiels Meredith S. , Lipkowitz Stanley , Campos Nicole G. , Schiffman Mark , Schiller John T. , Freedman Neal D. , Berrington de González Amy
Published: April 2023

Abstract
On February 2, 2022, President Biden and First Lady Dr. Biden reignited the Cancer Moonshot, setting a new goal to reduce age-standardized cancer mortality rates by at least 50% over the next 25 years in the United States. We estimated trends in U.S. cancer mortality during 2000 to 2019 for all cancers and the six leading types (lung, colorectum, pancreas, breast, prostate, liver). Cancer death rates overall declined by 1.4% per year from 2000 to 2015, accelerating to 2.3% per year during 2016 to 2019, driven by strong declines in lung cancer mortality (−4.7%/year, 2014 to 2019). Recent declines in colorectal (−2.0%/year, 2010–2019) and breast cancer death rates (−1.2%/year, 2013–2019) also contributed. However, trends for other cancer types were less promising. To achieve the Moonshot goal, progress against lung, colorectal, and breast cancer deaths needs to be maintained and/or accelerated, and new strategies for prostate, liver, pancreatic, and other cancers are needed. We reviewed opportunities to prevent, detect, and treat these common cancers that could further reduce population-level cancer death rates and also reduce disparities.
Significance:
We reviewed opportunities to prevent, detect, and treat common cancers, and show that to achieve the Moonshot goal, progress against lung, colorectal, and breast cancer deaths needs to be maintained and/or accelerated, and new strategies for prostate, liver, pancreatic, and other cancers are needed.

See related commentary by Bertagnolli et al., p. 1049.

This article is highlighted in the In This Issue feature, p. 1027
Comutations and KRASG12C Inhibitor Efficacy in Advanced NSCLC
Authors: Negrao Marcelo V. , Araujo Haniel A. , Lamberti Giuseppe , Cooper Alissa J. , Akhave Neal S. , Zhou Teng , Delasos Lukas , Hicks J. Kevin , Aldea Mihaela , Minuti Gabriele , Hines Jacobi , Aredo Jacqueline V. , Dennis Michael J. , Chakrabarti Turja , Scott Susan C. , Bironzo Paolo , Scheffler Matthias , Christopoulos Petros , Stenzinger Albrecht , Riess Jonathan W. , Kim So Yeon , Goldberg Sarah B. , Li Mingjia , Wang Qi , Qing Yun , Ni Ying , Do Minh Truong , Lee Richard , Ricciuti Biagio , Alessi Joao Victor , Wang Jing , Resuli Blerina , Landi Lorenza , Tseng Shu-Chi , Nishino Mizuki , Digumarthy Subba R. , Rinsurongkawong Waree , Rinsurongkawong Vadeerat , Vaporciyan Ara A. , Blumenschein George R. , Zhang Jianjun , Owen Dwight H. , Blakely Collin M. , Mountzios Giannis , Shu Catherine A. , Bestvina Christine M. , Garassino Marina Chiara , Marrone Kristen A. , Gray Jhanelle E. , Patel Sandip Pravin , Cummings Amy L. , Wakelee Heather A. , Wolf Juergen , Scagliotti Giorgio Vittorio , Cappuzzo Federico , Barlesi Fabrice , Patil Pradnya D. , Drusbosky Leylah , Gibbons Don L. , Meric-Bernstam Funda , Lee J. Jack , Heymach John V. , Hong David S. , Heist Rebecca S. , Awad Mark M. , Skoulidis Ferdinandos
Published: April 2023

Molecular modifiers of KRASG12C inhibitor (KRASG12Ci) efficacy in advanced KRASG12C-mutant NSCLC are poorly defined. In a large unbiased clinicogenomic analysis of 424 patients with non–small cell lung cancer (NSCLC), we identified and validated coalterations in KEAP1, SMARCA4, and CDKN2A as major independent determinants of inferior clinical outcomes with KRASG12Ci monotherapy. Collectively, comutations in these three tumor suppressor genes segregated patients into distinct prognostic subgroups and captured ∼50% of those with early disease progression (progression-free survival ≤3 months) with KRASG12Ci. Pathway-level integration of less prevalent coalterations in functionally related genes nominated PI3K/AKT/MTOR pathway and additional baseline RAS gene alterations, including amplifications, as candidate drivers of inferior outcomes with KRASG12Ci, and revealed a possible association between defective DNA damage response/repair and improved KRASG12Ci efficacy. Our findings propose a framework for patient stratification and clinical outcome prediction in KRASG12C-mutant NSCLC that can inform rational selection and appropriate tailoring of emerging combination therapies.

Significance:

In this work, we identify co-occurring genomic alterations in KEAP1, SMARCA4, and CDKN2A as independent determinants of poor clinical outcomes with KRASG12Ci monotherapy in advanced NSCLC, and we propose a framework for patient stratification and treatment personalization based on the comutational status of individual tumors.

See related commentary by Heng et al., p. 1513.

This article is highlighted in the In This Issue feature, p. 1501
Supplementary Figure 6 from Induction of PARP7 Creates a Vulnerability for Growth Inhibition by RBN2397 in Prostate Cancer Cells
Authors: Yang Chunsong , Wierbiłowicz Krzysztof , Dworak Natalia M. , Bae Song Yi , Tengse Sachi B. , Abianeh Nicki , Drake Justin M. , Abbas Tarek , Ratan Aakrosh , Wotton David , Paschal Bryce M.
Published: April 2023

Extendend analysis of PARP7 expression in prostate cancer
Diagnostic and Prognostic Performance of Plasma Albumin and Cholinesterase in Patients with Sepsis and Septic Shock
Authors: Schupp Tobias , Weidner Kathrin , Rusnak Jonas , Jawhar Schanas , Forner Jan , Dulatahu Floriana , Brück Lea Marie , Hoffmann Ursula , Bertsch Thomas , Müller Julian , Kittel Maximilian , Akin Ibrahim , Behnes Michael
Published: April 2023

Objective: Despite improved risk stratification tools and identification of novel biomarkers for the diagnosis and prognosis in patients with sepsis, sepsis-related mortality has not significantly improved during the past years. This study investigates the diagnostic and prognostic role of the plasma albumin and cholinesterase (ChE) in patients with sepsis and septic shock. Methods: Consecutive patients with sepsis and septic shock from 2019 to 2021 were included at one institution. Blood samples were obtained on the day of disease onset (day 1), and on days 2, 3, 5, and 7 thereafter. The diagnostic value of ChE for the diagnosis of a septic shock was compared to albumin and the prognostic value of the albumin and the ChE for 30-day all-cause mortality was tested. Results: 239 patients were included with a median albumin level of 21.4 g/dL and a median ChE of 5004 U/L on admission. With an area under the curve (AUC) of 0.641–0.762 on days 3 and 5, the ChE was associated with moderate but better diagnostic discrimination between sepsis and septic shock than albumin. Furthermore, ChE was able to discriminate between 30-day non-survivors and survivors (range of AUC 0.612–0.686). Patients with a ChE below the median had higher rates of 30-days all-cause mortality in comparison to patients with a ChE above the median (65 vs. 42%, log rank p = 0.001; HR = 1.820; 95% CI = 1.273–2.601; p = 0.001), which was still demonstrated after multivariable adjustment. Conclusion: The level of ChE was associated with moderate diagnostic and prognostic accuracy in patients with sepsis and septic shock, whereas albumin was not.