bluuebunny/crossref_metadata_2025_split huggingface dataset:
Krylov complexity of deformed conformal field theories
Authors: Chattopadhyay Arghya , Malvimat Vinay , Mitra Arpita 
Published: August 2024

Abstract
We consider a perturbative expansion of the Lanczos coefficients and the Krylov complexity for two-dimensional conformal field theories under integrable deformations. Specifically, we explore the consequences of $$ \textrm{T}\overline{\textrm{T}} $$
T

T
¯

, $$ \textrm{J}\overline{\textrm{T}} $$
J

T
¯

, and $$ \textrm{J}\overline{\textrm{J}} $$
J

J
¯

deformations, focusing on first-order corrections in the deformation parameter. Under $$ \textrm{T}\overline{\textrm{T}} $$
T

T
¯

deformation, we demonstrate that the Lanczos coefficients bn exhibit unexpected behavior, deviating from linear growth within the valid perturbative regime. Notably, the Krylov exponent characterizing the rate of exponential growth of complexity surpasses that of the undeformed theory for positive value of deformation parameter, suggesting a potential violation of the conjectured operator growth bound within the realm of perturbative analysis. One may attribute this to the existence of logarithmic branch points along with higher order poles in the autocorrelation function compared to the undeformed case. In contrast to this, both $$ \textrm{J}\overline{\textrm{J}} $$
J

J
¯

and $$ \textrm{J}\overline{\textrm{T}} $$
J

T
¯

deformations induce no first order correction to either the linear growth of Lanczos coefficients at large-n or the Krylov exponent and hence the results for these two deformations align with those of the undeformed theory.
Massive twistor worldline in electromagnetic fields
Authors: Kim Joon-Hwi , Kim Jung-Wook , Lee Sangmin 
Published: August 2024

Abstract
We study the (ambi-)twistor model for spinning particles interacting via electromagnetic field, as a toy model for studying classical dynamics of gravitating bodies including effects of both spins to all orders. We compute the momentum kick and spin kick up to one-loop order and show precisely how they are encoded in the classical eikonal. The all-orders-in-spin effects are encoded as a dynamical implementation of the Newman-Janis shift, and we find that the expansion in both spins can be resummed to simple expressions in special kinematic configurations, at least up to one-loop order. We confirm that the classical eikonal can be understood as the generator of canonical transformations that map the in-states of a scattering process to the out-states. We also remark that cut contributions for converting worldline propagators from time-symmetric to retarded amount to the iterated action of the leading eikonal at one-loop order.
Factors Influencing the Perceived Economic Benefits of Innovative Agri-Environmental Contracts
Authors: Bradfield Tracy , Harmanny Kina S. , Hennessy Thia , Schulp Catharina J. E. 
Published: August 2024

AbstractContinued innovation in contract design may enhance the delivery of agri-environmental climate public goods (AECPG), but barriers to adoption arise in terms of how farmers perceive the economic benefits. Therefore, this paper examines survey data from Ireland and the Netherlands to analyse whether land managers agree that results-based, collective action, value chain and land tenure contracts for the delivery of AECPG are understandable, applicable to their farm and economically beneficial. Using Probit models, we also identify groups of land managers who perceive the different contract types as being economically beneficial, and these findings can inform policymakers of farmer groups who need adequate consideration during the design of agri-environmental contracts. For example, greater incentives could encourage older farmers to enrol in results-based contracts in Ireland and value chain contracts in the Netherlands. We also find a link between contract duration and the perceived economic benefits of collective action contracts in both countries, with land managers in Ireland desiring a longer duration. We highlight that policymakers and land managers in Ireland could apply lessons from the design of agri-environmental contracts in the Netherlands, where they are more common and varied. Greater knowledge exchange between users and non-users of such contracts would also help bridge the gap between theory and practice in both countries.
Metaheuristic-based ensemble learning: an extensive review of methods and applications
Authors: Rezk Sahar Saeed , Selim Kamal Samy 
Published: August 2024

AbstractEnsemble learning has become a cornerstone in various classification and regression tasks, leveraging its robust learning capacity across disciplines. However, the computational time and memory constraints associated with almost all-learners-based ensembles necessitate efficient approaches. Ensemble pruning, a crucial step, involves selecting a subset of base learners to address these limitations. This study underscores the significance of optimization-based methods in ensemble pruning, with a specific focus on metaheuristics as high-level problem-solving techniques. It reviews the intersection of ensemble learning and metaheuristics, specifically in the context of selective ensembles, marking a unique contribution in this direction of research. Through categorizing metaheuristic-based selective ensembles, identifying their frequently used algorithms and software programs, and highlighting their uses across diverse application domains, this research serves as a comprehensive resource for researchers and offers insights into recent developments and applications. Also, by addressing pivotal research gaps, the study identifies exploring selective ensemble techniques for cluster analysis, investigating cutting-edge metaheuristics and hybrid multi-class models, and optimizing ensemble size as well as hyper-parameters within metaheuristic iterations as prospective research directions. These directions offer a robust roadmap for advancing the understanding and application of metaheuristic-based selective ensembles.
Residual feature decomposition and multi-task learning-based variation-invariant face recognition
Authors: Haider Abbas , Wu Guanfeng , Spence Ivor , Wang Hui 
Published: August 2024

AbstractFacial identity is subject to two primary natural variations: time-dependent (TD) factors such as age, and time-independent (TID) factors including sex and race. This study aims to address a broader problem known as variation-invariant face recognition (VIFR) by exploring the question: “How can identity preservation be maximized in the presence of TD and TID variations?" While existing state-of-the-art (SOTA) methods focus on either age-invariant or race and sex-invariant FR, our approach introduces the first novel deep learning architecture utilizing multi-task learning to tackle VIFR, termed “multi-task learning-based variation-invariant face recognition (MTLVIFR)." We redefine FR by incorporating both TD and TID, decomposing faces into age (TD) and residual features (TID: sex, race, and identity). MTLVIFR outperforms existing methods by 2% in LFW and CALFW benchmarks, 1% in CALFW, and 5% in AgeDB (20 years of protocol) in terms of face verification score. Moreover, it achieves higher face identification scores compared to all SOTA methods. Open source code.
The striking influence of solubility on the nuclearity of cobalt NCN pincer complexes
Authors: Käfer Matthias G. , Pecak Jan , Stöger Berthold , Kirchner Karl 
Published: August 2024

AbstractThe synthesis and characterization of two Co(II) complexes stabilized by NCN pincer ligands are described. The paramagnetic Co(II) complex [Co(κ3NCN-NCNCH2-iPr)Br] is obtained via a transmetalation protocol from CoBr2 and NC(C–Br)NCH2-iPr in THF. Surprisingly, the dinuclear complex [Co2(κ3NCN-μ2-NCNCH2-iPr)(μ-Cl)(Cl)2] was synthesized following the same synthetic protocol but using an ultrasonicated CoCl2 suspension instead of CoBr2 in the same solvent. Both complexes are paramagnetic species exhibiting solution magnetic moments of 1.9(1) and 5.8(3) μB, respectively. This corresponds to low-spin and high-spin d7 configurations featuring one and three unpaired electrons at the metal centers. X-ray structures of both complexes are presented.
Graphical abstract
Power utility maximization with expert opinions at fixed arrival times in a market with hidden Gaussian drift
Authors: Gabih Abdelali , Kondakji Hakam , Wunderlich Ralf 
Published: August 2024

AbstractIn this paper we study optimal trading strategies in a financial market in which stock returns depend on a hidden Gaussian mean reverting drift process. Investors obtain information on that drift by observing stock returns. Moreover, expert opinions in the form of signals about the current state of the drift arriving at fixed and known dates are included in the analysis. Drift estimates are based on Kalman filter techniques. They are used to transform a power utility maximization problem under partial information into an optimization problem under full information where the state variable is the filter of the drift. The dynamic programming equation for this problem is studied and closed-form solutions for the value function and the optimal trading strategy of an investor are derived. They allow to quantify the monetary value of information delivered by the expert opinions. We illustrate our theoretical findings by results of extensive numerical experiments.
Preclinical efficacy of oral and nasal rivastigmine-loaded chitosan nano-particles on AlCl3-induced Alzheimer’s-like disease in rats
Authors: ElMosbah Dina E. , Khattab Marwa S. , Ibrahim Marwa A. , El-Asssal Mona I. , Miniawy Hala M. F. El 
Published: August 2024

AbstractThe successful treatment of Alzheimer’s disease (AD) is still a big challenge. Rivastigmine is one of the most used drugs for the treatment of AD. The short half-life, lower bioavailability, and less concentration of the drug in the brain after oral delivery are considered the main drawbacks of rivastigmine. To improve these drawbacks, nanostructure-mediated drug delivery has gained more attention. This study investigates the effect of rivastigmine-loaded in optimized chitosan nano-particles (RS-CSNPs) as polymeric nano-carriers by different administration routes (oral and intranasal) on aluminum chloride (AlCl3)-induced Alzheimer-like disease in rat. The model was established by giving rats 100 mg/kg/b.wt of AlCl3 orally for 3 months. Then the experimental rats were treated with RS-CSNPs either orally or intranasally for 75 days. Histopathology, immunohistochemistry of Tau expression in brain tissue, and gene expression of Caspase-3, NF-κB, and Nrf-2 were carried out. The therapeutic agents used decreased the alterations observed in AlCl3 group with improvement in the neuronal viability. In addition to low expression of tau protein, down-regulation of caspase-3 and NF-κB genes and up-regulation of Nrf-2. RS-CSNPs alleviated the progression of AD presumably via blocking the inflammatory cascade and decreasing the oxidative stress process. The intranasal route is superior to the oral one and promising in AD management.
Genetic proxies for therapy of insulin drug targets and risk of osteoarthritis: a drug-target Mendelian randomization analysis
Authors: Cao Ziqin , Li Qiangxiang , Wu Jianhuang , Li Yajia 
Published: August 2024

Abstract
Background
The potential effects of insulin therapy on osteoarthritis (OA) risk are poorly understood. This study aimed to explore the causal relationship between insulin therapy and OA.

Methods
Mendelian randomization (MR) analysis was performed to examine the association between genetically proxied inhibition of insulin targets and the risk of overall, hip (HOA) and knee OA (KOA). We then performed univariable MR using summary statistics regarding insulin target genes derived from the DrugBank database. Data related to blood glucose reduction levels were used as a proxy for insulin levels. Two phenotypes, type 2 diabetes, and glycosylated hemoglobin levels, were selected as positive controls to confirm the direction and validity of the proxies. The OA datasets were derived from the UK Biobank cohort. Multivariable MR was adjusted for body mass index, sedentary behavior, cigarette smoking, frequency of alcohol intake, age, and genetic sex.

Results
Genetically proxied insulin therapy was associated with an increased risk of overall OA [odds ratio (OR):1.2595; 95% confidence interval (CI):1.0810–1.4675] and HOA (OR:1.4218; 95%CI:1.1240–1.7985), which remained consistent across multiple MR methods. After adjusting for confounders, we found evidence supporting a significant causal link with a higher risk of overall OA and HOA. A further two-step MR analysis revealed no significant mediation effects from the six mediators in the associations.

Conclusion
There was a causal association between genetically proxied insulin therapy and a higher risk of OA, especially HOA.
Parent-led Communication Therapy for Young Bilingual Autistic Children: A Scoping Review
Authors: Oudet Sarah , Howard Katie , Gilhuber Christina , Robert Marie , Zimmerli Joanna , Katsos Napoleon , Durrleman Stephanie 
Published: August 2024

AbstractA scoping review of the literature was undertaken using JBI guidelines to map the evidence of parent-led therapy (PLT) for young autistic children (≤ 6 years) raised in bilingual environments. Reviewers used Covidence to screen located sources. Sixteen papers met inclusion criteria. A strong acceleration of reports of PLT for young autistic children measured in bilingual environments was observed, with 93.8% of papers (n = 15) published since 2015. Reporting of participants’ language environments (home language(s)/L1s and societal language(s)/L2s) was inconsistent. A large majority of these studies, 87.5% (n = 14) were conducted in North America or in collaboration with a North American institution. Diverse PLT programs and methodologies were identified. There is variation in demographic information collected and outcomes reported. Evidence gaps in the literature are identified and the value of undertaking systematic review on this topic is considered. This scoping review points to the necessity of further empirical research and practice that centres parents in early and specific support for autistic children raised in bilingual environments. Suggestions for improving reporting standards of language profiles are provided.
The Predictive Power of Religious Coping on Care Burden, Depression, Stress, and Anxiety of Parents of Pediatric Oncology Patients in Turkey
Authors: Semerci Remziye , Uysal Gülzade , Açikgöz Ayfer , Demirer Pınar 
Published: August 2024

AbstractThis study aimed to determine the predictive power of religious coping of parents of children with cancer on caregiver burden, depression, anxiety, and stress in Turkey. It was designed as a descriptive and cross-sectional study, utilizing correlational analysis and regression models to explore associations between variables. Data were collected from 164 parents in the pediatric hematology-oncology clinics of a university hospital between November 2023 and March 2024. There was a negative correlation between caregiver burden score and negative and positive religious coping scores. Caregiver burden scores were positively correlated with depression, anxiety, and stress scores. Results indicated that caregiver burden, education level, employment status, family structure, family income, and age at diagnosis significantly predicted positive religious coping. For negative religious coping, caregiver burden, education level, family structure, and family income were significant predictors. This suggests that religious coping may help reduce caregiver burden, underscoring the importance of promoting constructive coping strategies to support caregivers' well-being.
Uncertainty Quantification in Mineral Resource Estimation
Authors: Lindi Oltingey Tuya , Aladejare Adeyemi Emman , Ozoji Toochukwu Malachi , Ranta Jukka-Pekka 
Published: August 2024

AbstractMineral resources are estimated to establish potential orebody with acceptable quality (grade) and quantity (tonnage) to validate investment. Estimating mineral resources is associated with uncertainty from sampling, geological heterogeneity, shortage of knowledge and application of mathematical models at sampled and unsampled locations. The uncertainty causes overestimation or underestimation of mineral deposit quality and/or quantity, affecting the anticipated value of a mining project. Therefore, uncertainty is assessed to avoid any likely risks, establish areas more prone to uncertainty and allocate resources to scale down potential consequences. Kriging, probabilistic, geostatistical simulation and machine learning methods are used to estimate mineral resources and assess uncertainty, and their applicability depends on deposit characteristics, amount of data available and expertise of technical personnel. These methods are scattered in the literature making them challenging to access when needed for uncertainty quantification. Therefore, this review aims to compile information about uncertainties in mineral resource estimation scatted in the literature and develop a knowledge base of methodologies for uncertainty quantification. In addition, mineral resource estimation comprises different interdependent steps, in and through which uncertainty accumulates and propagates toward the final estimate. Hence, this review demonstrates stepwise uncertainty propagation and assessment through various phases of the estimation process. This can broaden knowledge about mineral resource estimation and uncertainty assessment in each step and increase the accuracy of mineral resource estimates and mining project viability.
A generalized Bouc–Wen model for simulating the quasi-static and dynamic shear responses of helical wire rope isolators
Authors: Capuano Raffaele , Vaiana Nicoló , Carboni Biagio 
Published: August 2024

AbstractThis research investigates the mechanical behavior of a helical wire rope isolator deforming along its shear direction. In particular, we present the results of an extensive experimental campaign including both quasi-static and dynamic tests. The former provide hysteresis loops characterizing the device quasi-static behavior; the latter, performed by using an electro-mechanical shaker, furnish frequency response curves describing the dynamic behavior of a rigid block supported by the tested device. To simulate such a complex behavior, we adopt a generalized Bouc–Wen model and identify its parameters on the basis of the quasi-static test results. Subsequently, such a model is employed to reproduce the frequency response curves of the isolated rigid block. Since the results of the dynamic tests suggest the presence of rate-dependent hysteresis phenomena in the isolated system, the generalized Bouc–Wen model is enhanced by introducing a linear viscous component. Finally, to substantiate the model validation, the experimental results obtained by applying a series of white noise signals are compared with those obtained numerically to demonstrate the model capability of reproducing the device behavior in non-stationary response conditions.
Crop stress detection from UAVs: best practices and lessons learned for exploiting sensor synergies
Authors: Chakhvashvili Erekle , Machwitz Miriam , Antala Michal , Rozenstein Offer , Prikaziuk Egor , Schlerf Martin , Naethe Paul , Wan Quanxing , Komárek Jan , Klouek Tomáš , Wieneke Sebastian , Siegmann Bastian , Kefauver Shawn , Kycko Marlena , Balde Hamadou , Paz Veronica Sobejano , Jimenez-Berni Jose A. , Buddenbaum Henning , Hänchen Lorenz , Wang Na , Weinman Amit , Rastogi Anshu , Malachy Nitzan , Buchaillot Maria-Luisa , Bendig Juliane , Rascher Uwe 
Published: August 2024

Introduction
Detecting and monitoring crop stress is crucial for ensuring sufficient and sustainable crop production. Recent advancements in unoccupied aerial vehicle (UAV) technology provide a promising approach to map key crop traits indicative of stress. While using single optical sensors mounted on UAVs could be sufficient to monitor crop status in a general sense, implementing multiple sensors that cover various spectral optical domains allow for a more precise characterization of the interactions between crops and biotic or abiotic stressors. Given the novelty of synergistic sensor technology for crop stress detection, standardized procedures outlining their optimal use are currently lacking.

Materials and methods
This study explores the key aspects of acquiring high-quality multi-sensor data, including the importance of mission planning, sensor characteristics, and ancillary data. It also details essential data pre-processing steps like atmospheric correction and highlights best practices for data fusion and quality control.

Results
Successful multi-sensor data acquisition depends on optimal timing, appropriate sensor calibration, and the use of ancillary data such as ground control points and weather station information. When fusing different sensor data it should be conducted at the level of physical units, with quality flags used to exclude unstable or biased measurements. The paper highlights the importance of using checklists, considering illumination conditions and conducting test flights for the detection of potential pitfalls.

Conclusion
Multi-sensor campaigns require careful planning not to jeopardise the success of the campaigns. This paper provides practical information on how to combine different UAV-mounted optical sensors and discuss the proven scientific practices for image data acquisition and post-processing in the context of crop stress monitoring.
A bibliometric study of positive psychological capital: investigating intellectual foundations through co-citation and content analyses
Authors: Reichard Rebecca J. , Smith Daniel J. , Avey James B. , Mhatre Ketan H. 
Published: August 2024

AbstractSince its inception in the early 2000s, the growing popularity of positive psychological capital (i.e., PsyCap) has been accompanied by robust debates. Critics assert that PsyCap research is plagued by suboptimal theoretical foundations, disregard for rigorous methodologies, and cult-like cronyism. Leveraging bibliometric data based on 937 primary documents, 28,428 secondary documents, 9714 sources, and 18,247 authors, we conduct document, source, and author co-citation analyses to examine the intellectual foundations of PsyCap and, thus, the veracity of these critiques. We extend this comprehensive scientific mapping of the PsyCap field with an in-depth content analysis of the 100 most frequently co-cited secondary documents. Results suggest that the PsyCap field is built upon solid theoretical foundations in psychology published in reputable, peer-reviewed journals. The authors of secondary documents consider the typical organizational behavior methodological approaches, emphasizing correlational designs. And, although somewhat insular, the research that underlies the PsyCap field consists of a distribution of contributing authors and journals. Finally, we discuss implications for the practical application of positive psychology tenets and prescriptions for scholars researching PsyCap.