bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improved dynamic kernelPCAbased on local preserving projections and its application for electric submersible pump fault diagnosis
Authors: Gao Xiaoyong , Zhang Yu , Zhou Junfeng 
Published: November 2022

AbstractDynamic kernel principal component analysis (DKPCA) has been frequently implemented for nonlinear and dynamic process monitoring of complex industrial processes. However, traditional DKPCA focuses only on the global structural analysis of data sets and strongly neglects the local information, which is equally essential for process detection and identification. In this paper, an improved DKPCA, referred to as the local DKPCA (LDKPCA), is proposed based on local preserving projections (LPP) for nonlinear dynamic process fault diagnosis. The method combines the advantages of LPP and DKPCA by utilizing the local structure feature to maintain the geometric structure of the data in a unified framework. To achieve a highly comprehensive feature extraction, the local characteristics are fused in DKPCA to produce an optimization objective. The neighbouring points of the new objective function projection in the feature space are still maintained in proximity, and the variance information is retained simultaneously. For the purpose of fault detection, two statistics, known as theT2and squared prediction error (SPE) statistics, are constructed, based on the LDKPCA model, and used to monitor the latent variable space and the residual space, respectively. In addition, the sensitivity analysis is brought in for fault identification of the two statistics. Based on the experimental analysis using the shaft breakage data of an offshore oilfield electric submersible pump (ESP), the proposed method outperforms the conventional DKPCA in terms of fault monitoring performance. The experimental results demonstrate the potential of the method in nonlinear dynamic process fault diagnosis.
Potentially inappropriate medications in geriatric blood or marrow transplantation (BMT) survivors: A BMT Survivor Study report
Authors: Sanchez‐Luege Sebastian , Landier Wendy , Dai Chen , Hageman Lindsey , Ross Elizabeth S. , Balas Nora A. , Bosworth Alysia , Te Hok Sreng , Wu Jessica , Francisco Liton , Wong F. Lennie , Forman Stephen J. , Armenian Saro H. , Weisdorf Daniel J. , Bhatia Smita 
Published: November 2022

AbstractBackgroundBlood or marrow transplantation (BMT) is increasingly offered to older individuals with hematologic malignancies. The high prevalence of chronic health conditions in such individuals necessitates use of multiple medications. Beers Criteria represent a list of potentially inappropriate medications (PIMs) shown to increase the risk of health problems in the elderly. We sought to determine the prevalence and predictors of PIM use in older BMT survivors and identify associations with health problems.MethodsStudy participants were drawn from the BMT Survivor Study, a cohort study of patients transplanted at three US transplant centers between 1974 and 2014 and surviving ≥2 years. For this report, the survivors were aged ≥65 years. Siblings served as a comparison group. Participants self‐reported sociodemographics, chronic health conditions, and medication use. Logistic regression analyses identified predictors of PIM use and associations with health problems.ResultsOverall, PIM use was comparable between BMT survivors (49.4%) and siblings (49.3%) (odds ratio [OR] = 0.9; 95% CI, 0.7–1.2); however, BMT survivors were more likely to use >1 PIM (17.4% vs. 12.4%; OR = 1.5; 95% CI, 1.01–2.4) and central nervous system–related PIMs (8.3% vs. 4.3%; OR = 2.18; 95% CI, 1.17–4.09). Predictors of PIM use included presence of severe/life‐threatening chronic health conditions (OR = 1.5; 95% CI, 1.1–2.0), and chronic graft versus host disease (OR = 1.7; 95% CI, 1.1–2.7). Survivors taking >1 PIM reported more issues with vertigo (OR = 2.3; 95% CI, 1.1–4.7), balance (OR = 2.6; 95% CI, 1.7–4.1), faintness/dizziness (OR = 2.8; 95% CI, 1.8–4.6), and personal care (OR = 4.5; 95% CI, 1.4–14.8).ConclusionsThis study shows the health problems associated with PIM use and identifies vulnerable populations at higher risk for PIM use, providing evidence for caution in using PIMs in high‐risk populations.
Pulse coupled neural network optimized with chaotic grey wolf algorithm for breast cancer classification using mammogram images
Authors: Thanupillai Kalai Selvi , Kamal Basha Rahimunnisa 
Published: November 2022

SummaryBreast cancer is a very hazardous disease that mainly affects women and leads to a high mortality rate. Early detection of this disease only can reduce the mortality rate. Previously, several methods were used to detect this cancer, but none of them provides sufficient accuracy. To deal this issue, a pulse coupled neural network optimized with chaotic grey wolf algorithm is proposed in this article for the classification of breast cancer using mammogram images. The breast cancer images are gathered from MAMMOSET dataset. The images are preprocessed and segmented with the help of Tsalli's entropy based multilevel 3D Otsu (TE‐3D‐Otsu) thresholding method. Then the parameters of the TE‐3D‐Otsu are optimized using the improved shuffled shepherd optimization algorithm. The features are extracted using moment invariant wavelet feature extraction technique. The images are classified using pulse coupled neural network (PCNN). Then, PCNN mass parameters are optimizes utilizing chaotic grey wolf optimization algorithm (chaotic‐GWOA) for categorizing the mammogram breast cancer imageries, such as malignant, benign, and normal. The proposed method is activated on MATLAB, its performance is analyzed with existing methods. The simulation results show that the proposed BC‐PCNN‐CGWOA attains the accuracy 57.86%, 85.94%, and 53.45% is greater than the existing methods.
Raven finch optimized deep convolutional neural network model for intra‐frame video forgery detection
Authors: Singla Neetu , Singh Jyotsna , Nagpal Sushama 
Published: November 2022

SUMMARYDue to the tremendous growth of video editing software, it has become extremely simple to introduce malicious content by manipulating multimedia data. This may include modification of videos either by adding or deleting selective frames with malicious intentions. Hence, it is essential to find the forged frames of the videos by introducing efficient and reliable video forensic methods. This article presents an automatic intra‐frame video forgery detection strategy based on a hybrid optimization tuned deep‐convolutional neural network (deep‐CNN) classifier. The significance of the proposed method lies in developing the proposed raven‐finch optimization algorithm that tunes the weights of the deep‐CNN to exhibit enhanced detection accuracy. The proposed raven‐finch optimization algorithm combines raven search agents and finches search agents, possessing the benefits of both search agents. The features of the input video frames act as the input to the deep‐CNN classifier that detects forgery. The performance of the proposed raven‐finch‐based deep CNN method is analyzed in terms of the performance indices, such as accuracy, sensitivity, and specificity. It is attained to be 97.56%, 95.48%, and 96.38%, respectively, which shows the superiority of the proposed method for intra‐frame forgery detection.
Confidence in nicotine for tobacco harm reduction—Bridging the policy–practice gap
Authors: Patwardhan Sudhanshu 
Published: November 2022

AbstractDecades of research show that constituents other than nicotine are the harmful agents in tobacco products. This knowledge is incorporated into the nicotine regulatory policies of countries leading in tobacco control, such as the UK and New Zealand. Alternative nicotine products, such as nicotine replacement therapy and e‐cigarettes, are now endorsed in the UK by a number of healthcare bodies in a tobacco harm reduction approach that encourages tobacco users to completely switch to a less risky nicotine‐containing product. The potential role of ‘clean’ nicotine alternatives to reduce the harms from tobacco is, however, not being translated into practice. Many healthcare practitioners still bundle tobacco, cigarettes, smoking, cancer and nicotine into one, thus preventing them from supporting their patients to make informed choices on safer nicotine alternatives. This misperception among healthcare professionals, in turn, is a hurdle to effective tobacco control policymaking in many low‐ and middle‐income countries and effective cessation support everywhere in the world. Nicotine confidence based on nicotine literacy among the key decision‐makers should start with reforming medical curricula and myth‐busting in the lay media to include factual statements about nicotine and public health policy discussions on the principles of harm reduction.
Moving past the challenges and misconceptions in urban adaptation research
Authors: Winchell Kristin M. , Aviles‐Rodriguez Kevin J. , Carlen Elizabeth J. , Miles Lindsay S. , Charmantier Anne , De León Luis F. , Gotanda Kiyoko M. , Rivkin L. Ruth , Szulkin Marta , Verrelli Brian C. 
Published: November 2022

AbstractAlthough the field of urban evolutionary ecology has recently expanded, much progress has been made in identifying adaptations that arise as a result of selective pressures within these unique environments. However, as studies within urban environments have rapidly increased, researchers have recognized that there are challenges and opportunities in characterizing urban adaptation. Some of these challenges are a consequence of increased direct and indirect human influence, which compounds long‐recognized issues with research on adaptive evolution more generally. In this perspective, we discuss several common research challenges to urban adaptation related to (1) methodological approaches, (2) trait–environment relationships and the natural history of organisms, (3) agents and targets of selection, and (4) habitat heterogeneity. Ignoring these challenges may lead to misconceptions and further impede our ability to draw conclusions regarding evolutionary and ecological processes in urban environments. Our goal is to first shed light on the conceptual challenges of conducting urban adaptation research to help avoid the propagation of these misconceptions. We further summarize potential strategies to move forward productively to construct a more comprehensive picture of urban adaptation, and discuss how urban environments also offer unique opportunities and applications for adaptation research.
The ecology and quantitative genetics of seed and seedling traits in upland and lowland ecotypes of a perennial grass
Authors: Razzaque Samsad , Juenger Thomas E. 
Published: November 2022

AbstractPlants have evolved diverse reproductive allocation strategies and seed traits to aid in dispersal, persistence in the seed bank, and establishment. In particular, seed size, dormancy, and early seedling vigor are thought to be key functional traits with important recruitment and fitness consequences across abiotic stress gradients. Selection for favored seed-trait combinations, or against maladaptive combinations, is likely an important driver shaping recruitment strategies. Here, we test for seed-trait plasticity and patterns of recruitment using two genotypes representative of contrasting upland and lowland ecotypes of Panicum hallii with field experiments in native versus foreign habitats. Furthermore, we test whether seed traits have been under directional selection in P. hallii using the v-test based on trait variance in a genetic cross. Finally, we evaluate the genetic architecture of ecotypic divergence for these traits with quantitative trait locus (QTL) mapping. Field experiments reveal little plasticity but support a hypothesis of adaptation divergence among ecotypes based on recruitment. Patterns of segregation within recombinant hybrids provides strong support for directional selection driving ecotypic divergence in seed traits. Genetic mapping revealed a polygenic architecture with evidence of genetic correlation between seed mass, dormancy, and seedling vigor. Our results suggest that the evolution of these traits may involve constraints that affect the direction of adaptive divergence. For example, seed size and germination percentage shared two colocalized QTL with antagonistic additive effects. This supports the hypothesis of a functional genetic relationship between these traits, resulting in either large seed/strong dormancy or small seed/weak dormancy trait combinations. Overall, our study provides insights into the factors facilitating and potentially constraining ecotypic differentiation in seed traits.
Determination of the barrier height of a crystalline dipolar molecular rotor directly from temperature‐dependent dielectric spectra
Authors: Fujimura Yuichi , Teranishi Yoshiaki 
Published: November 2022

AbstractAn explicit relation between half‐width at half‐maximum ΔT in a dissipation factor of dipolar molecular rotors in a solid phase and rotational barrier height Ub was derived within the Debye relaxation model. The formula for Ub is simply expressed as . Here, T* is the temperature at the peak position in the dissipation factor, and k is the Boltzmann constant. The formula is an alternative to the familiar Arrhenius equation, from which Ub has so far been estimated in various dielectric experiments. The distinction of the proposed formula is the determination of Ub from a single peak in a dissipation factor induced by an electric field, while the Arrhenius equation needs data for the magnitudes of the dissipation factor and temperatures at several peaks. By applying the proposed formula to dipole molecular rotors (ROT‐2F) in a single crystalline and polycrystalline, for which Ub values were reported (Horansky et al., Phys. Rev. B 74, 054306 [2006]), the calculated values of Ub were quantitatively reproduced. This indicates the validity of the proposed formula, and the formula is expected to be applied to the analysis of dielectric spectra of 2D dipolar molecular rotor systems.
Spontaneous thought characteristics are differentially related to heightened negative affect versus blunted positive affect in adolescents: An experience sampling study
Authors: Webb Christian A. , Tierney Anna O. , Brown Hallie A. , Forbes Erika E. , Pizzagalli Diego A. , Ren Boyu 
Published: November 2022

AbstractBackgroundMind‐wandering has been linked to negative affect (NA) and depressive symptoms in adolescents. However, mind‐wandering is an extremely broad and heterogeneous cognitive construct. Some features of spontaneous thought may be related to increased NA, whereas others may improve affect, or have no emotional influence. We used ecological momentary assessment (EMA) to investigate the characteristics of spontaneous thoughts in adolescents and their differential relations with moment‐to‐moment affect.MethodOne‐hundred and sixteen adolescents (ages 13–18; Typical Mood [TM] = 58; Low Mood [LM] = 58) completed 5 days (2–3 times/day) of EMA (total 1037 surveys) assessing current positive affect (PA) and NA and dimensions of spontaneous thought. Multilevel models tested the relation between thought characteristics and affect.ResultsRelative to the TM group, LM adolescents had a higher frequency of mind‐wandering (38% vs. 56%) and negatively‐valanced thoughts during episodes of mind‐wandering (21% vs. 37%). Negatively‐valenced, self‐referential and past‐oriented thoughts were each associated with higher NA, even when controlling for plausible confounds (e.g., engagement in an unpleasant activity or social interaction, depressive symptom severity). In contrast, task‐focused and positively‐valenced thoughts were uniquely linked to higher PA.ConclusionCharacteristics of spontaneous thought—including temporal orientation, self‐referential quality, and task‐relatedness—were differentially related to NA versus PA in adolescents. If replicated, these findings could inform more nuanced assessments of and targeted interventions for specific dimensions of mind‐wandering contributing to high NA versus blunted PA in teens.
Efficacy analysis of different FLT3 inhibitors in patients with relapsed/refractory acute myeloid leukemia and high‐risk myelodysplastic syndrome
Authors: Swaminathan Mahesh , Aly Mai M. , Khan Abdul Moiz , Share Bayan Al , Dhillon Vikram , Lalo Enxhi , Ramos Harry , Akers Katherine G. , Kim Seongho , Balasubramanian Suresh 
Published: November 2022

AbstractSeveral FLT3 inhibitors(i) are available to treat relapsed/refractory (R/R) FLT3‐internal tandem duplicated acute myeloid leukemia (AML). This study analyzes the efficacies of various FLT3i (types 1 and 2) tested in clinical trials in treating R/R AML and high‐risk myelodysplastic syndromes (HR‐MDS). PubMed and EMBASE databases were searched for single/double‐arm phase I/II/III R/R AML or HR‐MDS clinical trials published between 1/1/2000 and 6/1/2021. The outcomes studied were composite response rate (CRc) and overall response rate (ORR). Toxicities were compared based on the organ system. The 28 studies analyzed had 1927 patients. The pooled ORR and (CRc) for all FLT3i were 53% (95% CI, 43%–63%) and 34% (95% CI, 26%–44%). Pooled ORR and CRc were 37% (95% CI, 25%–51%) and 35% (95% CI, 21%–52%) for type 1 and 58% (95% CI, 43%–71%) and 38% (95% CI, 27%–50%) for type 2, respectively. Gastrointestinal (GI) and hematological toxicity occurred in 22% (95% CI, 19%–25.4%) and 74.6% (95% CI, 70%–79%) with type 1 and 13.9% (95% CI, 12%–16%) and 57.7% (95% CI, 54.6%–60.8%) with type 2 FLT3i. QTc prolongation occurred in 2.06% (95% CI, 1.03%–3.65%) with type 1 and 7% (95% CI, 5.3%–9%) with type 2 FLT3i. Type 2 FLT3i had less GI toxicity but more QTc prolongation. Prospective studies are needed to compare the efficacy of type 1 and 2 FLT3i.
Exploration of Interstitial Fibrosis in Chronic Kidney Disease by Diffusion‐Relaxation Correlation Spectrum MR Imaging: A Preliminary Study
Authors: Liu Fang , Hu Wentao , Sun Yawen , Shen Yiwei , Zhou Wenyan , Dai Yongming , Gu Leyi , Zhang Minfang , Zhou Yan 
Published: November 2022

BackgroundRenal interstitial fibrosis is one of the most common pathways in the progression of chronic kidney disease (CKD). Noninvasive evaluation of interstitial fibrosis would help monitoring CKD progression and prognosis prediction.PurposeTo evaluate the severity of renal interstitial fibrosis by diffusion‐relaxation correlation spectrum imaging (DR‐CSI).Study TypeProspective.SubjectsForty patients with CKD and 10 healthy controls (average age 49.2 ± 14.8 years, 18 females).Field Strength/Sequence3‐T, DR‐CSI with 36 axial spin‐echo echo‐planar diffusion‐weighted images (6 b‐values, 6 echo times).AssessmentInterstitial fibrosis level (IFL) was assessed from biopsy results (IFL = 1, fibrosis percentage <25%, defined as mild; IFL = 2, 25%–50%, moderate; IFL = 3, >50%, severe). Estimated glomerular filtration rate (eGFR) was calculated using serum creatinine. The regions of interest included cortex for both kidneys. The diffusivity‐T2 spectrum was assessed considering three compartments (threshold: T2 30–40 msec, diffusivity 5–9 μm2/msec, according to visible peaks): A (low diffusivity, short T2), B (low diffusivity, long T2), and C (high diffusivity). Volume fractions Vi (i = A, B, C) were calculated.Statistical TestsIntra‐class coefficient (ICC, >0.6 as good) to assess inter‐reader agreement of DR‐CSI Vi. Spearman's correlation to assess relationship of Vi to IFL and eGFR. Receiver operating characteristic analyses with the area under the curve (AUC) to discriminate patients with moderate‐severe fibrosis from mild ones. Statistical significance criteria: P‐value <0.05.ResultsICCs were good for all Vi. Correlations were found between IFL and VB (r = 0.424, significant) and VC (r = −0.400, significant), and between eGFR and VB (r = −0.303, P = 0.058) and VC (r = 0.487, significant). Regarding VB and VC, the AUCs were 0.903 and 0.824.Data ConclusionDR‐CSI help distinguish patients with moderate or severe renal interstitial fibrosis from mild ones.Evidence Level: 2Technical Efficacy: Stage 2
Automatic 3D CT liver segmentation based on fast global minimization of probabilistic active contour
Authors: Jin Renchao , Wang Manyang , Xu Lijun , Lu Jiayi , Song Enmin , Ma Guangzhi 
Published: November 2022

AbstractPurposeAutomatic liver segmentation from computed tomography (CT) images is an essential preprocessing step for computer‐aided diagnosis of liver diseases. However, due to the large differences in liver shapes, low‐contrast to adjacent tissues, and existence of tumors or other abnormalities, liver segmentation has been very challenging. This study presents an accurate and fast liver segmentation method based on a novel probabilistic active contour (PAC) model and its fast global minimization scheme (3D‐FGMPAC), which is explainable as compared with deep learning methods.MethodsThe proposed method first constructs a slice‐indexed‐histogram to localize the volume of interest (VOI) and estimate the probability that a voxel belongs to the liver according its intensity. The probabilistic image would be used to initialize the 3D PAC model. Secondly, a new contour indicator function, which is a component of the model, is produced by combining the gradient‐based edge detection and Hessian‐matrix‐based surface detection. Then, a fast numerical scheme derived for the 3D PAC model is performed to evolve the initial probabilistic image into the global minimizer of the model, which is a smoothed probabilistic image showing a distinctly highlighted liver. Next, a simple region‐growing strategy is applied to extract the whole liver mask from the smoothed probabilistic image. Finally, a B‐spline surface is constructed to fit the patch of the rib cage to prevent possible leakage into adjacent intercostal tissues.ResultsThe proposed method is evaluated on two public datasets. The average Dice score, volume overlap error, volume difference, symmetric surface distance and volume processing time are 0.96, 7.35%, 0.02%, 1.17 mm and 19.8 s for the Sliver07 dataset, and 0.95, 8.89%, , 1.45 mm and 23.08 s for the 3Dircadb dataset, respectively.ConclusionsThe proposed fully‐automatic approach can effectively segment the liver from low‐contrast and complex backgrounds. The quantitative and qualitative results demonstrate that the proposed segmentation method outperforms state‐of‐the‐art traditional automatic liver segmentation algorithms and achieves very competitive performance compared with recent deep leaning‐based methods.
Formulations and valid inequalities for the capacitated dispersion problem
Authors: Landete Mercedes , Peiró Juanjo , Yaman Hande 
Published: November 2022

AbstractThis work focuses on the capacitated dispersion problem for which we study several mathematical formulations in different spaces using variables associated with nodes, edges, and costs. The relationships among the presented formulations are investigated by comparing the projections of the feasible sets of the LP relaxations onto the subspace of natural variables. These formulations are then strengthened with families of valid inequalities and variable‐fixing procedures. The separation problems associated with the valid inequalities that are exponential in number are shown to be polynomially solvable by reducing them to longest path problems in acyclic graphs. The dual bounds obtained from stronger but larger formulations are used to improve the strength of weaker but smaller formulations. Several sets of computational experiments are conducted to illustrate the usefulness of the findings, as well as the aptness of the formulations for different types of instances.