bluuebunny/crossref_metadata_2025_split huggingface dataset:
Novelty and learning in cognitive control: evidence from the Simon task
Authors: De Cesarei Andrea , D’Ascenzo Stefania , Nicoletti Roberto , Codispoti Maurizio 
Published: April 2023

AbstractWhile information that is associated with inappropriate responses can interfere with an ongoing task and be detrimental to performance, cognitive control mechanisms and specific contextual conditions can alleviate interference from unwanted information. In the spatial correspondence (Simon) task, interference has been consistently shown to be reduced by spatial non-correspondence in the previous trial (i.e., correspondence sequence effect, CSE); however the mechanisms supporting this sequential effect are not well understood. Here we investigated the role of novelty and trial-to-trial changes in stimulus and response features in a Simon task, observing similar modulation of CSE for novel and non-novel stimulus changes. However, changing the response modality from trial to trial dampened CSE, and this dampening was more pronounced when the probability of switch trials was higher, suggesting a role for long-term learning. The results are consistent with recent accounts, which indicate that spatial interference can be prevented by cognitive control mechanisms triggered by learned bindings.
Semi-supervised invertible neural operators for Bayesian inverse problems
Authors: Kaltenbach Sebastian , Perdikaris Paris , Koutsourelakis Phaedon-Stelios 
Published: April 2023

AbstractNeural Operators offer a powerful, data-driven tool for solving parametric PDEs as they can represent maps between infinite-dimensional function spaces. In this work, we employ physics-informed Neural Operators in the context of high-dimensional, Bayesian inverse problems. Traditional solution strategies necessitate an enormous, and frequently infeasible, number of forward model solves, as well as the computation of parametric derivatives. In order to enable efficient solutions, we extend Deep Operator Networks (DeepONets) by employing a RealNVP architecture which yields an invertible and differentiable map between the parametric input and the branch-net output. This allows us to construct accurate approximations of the full posterior, irrespective of the number of observations and the magnitude of the observation noise, without any need for additional forward solves nor for cumbersome, iterative sampling procedures. We demonstrate the efficacy and accuracy of the proposed methodology in the context of inverse problems for three benchmarks: an anti-derivative equation, reaction-diffusion dynamics and flow through porous media.
Solving the hierarchical windy postman problem with variable service costs using a math-heuristic algorithm
Authors: Keskin Muhammed Emre , Yılmaz Mustafa , Triki Chefi 
Published: April 2023

AbstractThe Hierarchical Windy Postman Problem (HWPP) is an arc routing problem in which an order relation is imposed on the arcs/edges of the graph, and one has to pass through each edge at least once while adhering to the hierarchical priority relations. The tour starts from and ends at a specific node and the aim is to minimize the length of the tour. We consider a variant of the HWPP in which (i) the precedence order of the edge hierarchies is linear and edges within each hierarchy are connected and (ii) the cost of serving each edge decreases with the number of times it is traversed, and we refer to it as HWPP with variable service costs. An integer non-heuristic linear mathematical formulation is proposed, and a solution approach is designed. Our solution heuristic adapts the layer algorithm of Dror et al. (Networks 17:283–294, 1987) but employs an integer mathematical formulation as a sub-procedure instead of the blossom algorithm to find the least cost path between the nodes of the graph. This choice is based on the fact that the blossom algorithm requires a symmetric cost structure while we deal here with the general case of asymmetric cost structure, which makes our problem a windy variant of the postman problem. It should be noted that our problem is not asymmetric in the sense that there are no opposite arcs with different costs but there are edges which have different costs depending on the traversal direction. In order to compare the performance of our heuristic algorithm with respect to the performance of the mathematical model that is solved by the commercial solver Gurobi, 84 test instances are generated having varying sizes and densities and with different number of hierarchies. These test instances are solved by both methods and the generated results show that the proposed heuristic method is much faster and generates better quality solutions.
Multi-objective chaos game optimization
Authors: Khodadadi Nima , Abualigah Laith , Al-Tashi Qasem , Mirjalili Seyedali 
Published: April 2023

AbstractThe Chaos Game Optimization (CGO) has only recently gained popularity, but its effective searching capabilities have a lot of potential for addressing single-objective optimization issues. Despite its advantages, this method can only tackle problems formulated with one objective. The multi-objective CGO proposed in this study is utilized to handle the problems with several objectives (MOCGO). In MOCGO, Pareto-optimal solutions are stored in a fixed-sized external archive. In addition, the leader selection functionality needed to carry out multi-objective optimization has been included in CGO. The technique is also applied to eight real-world engineering design challenges with multiple objectives. The MOCGO algorithm uses several mathematical models in chaos theory and fractals inherited from CGO. This algorithm's performance is evaluated using seventeen case studies, such as CEC-09, ZDT, and DTLZ. Six well-known multi-objective algorithms are compared with MOCGO using four different performance metrics. The results demonstrate that the suggested method is better than existing ones. These Pareto-optimal solutions show excellent convergence and coverage.
An automatic improved facial expression recognition for masked faces
Authors: ELsayed Yasmeen , ELSayed Ashraf , Abdou Mohamed A. 
Published: April 2023

AbstractAutomatic facial expression recognition (AFER), sometimes referred to as emotional recognition, is important for socializing. Automatic methods in the past two years faced challenges due to Covid-19 and the vital wearing of a mask. Machine learning techniques tremendously increase the amount of data processed and achieved good results in such AFER to detect emotions; however, those techniques are not designed for masked faces and thus achieved poor recognition. This paper introduces a hybrid convolutional neural network aided by a local binary pattern to extract features in an accurate way, especially for masked faces. The basic seven emotions classified into anger, happiness, sadness, surprise, contempt, disgust, and fear are to be recognized. The proposed method is applied on two datasets: the first represents CK and CK +, while the second represents M-LFW-FER. Obtained results show that emotion recognition with a face mask achieved an accuracy of 70.76% on three emotions. Results are compared to existing techniques and show significant improvement.
Thermodynamics of the Spin Square
Authors: Schmidt Heinz-Jürgen , Schröder Christian 
Published: April 2023

AbstractSmall spin systems at the interface between analytical studies and experimental application have been intensively studied in recent decades. The spin ring consisting of four spins with uniform antiferromagnetic Heisenberg interaction is an example of a completely integrable system, in the double sense: quantum mechanical and classical. However, this does not automatically imply that the thermodynamic quantities of the classical system can also be calculated explicitly. In this work, we derive analytical expressions for the density of states, the partition function, specific heat, entropy, and susceptibility. These theoretical results are confirmed by numerical tests. This allows us to compare the quantum mechanical quantities for increasing spin quantum numbers s with their classical counterparts in the classical limit $$s\rightarrow \infty $$

s
→
∞

. As expected, a good agreement is obtained, except for the low temperature region. However, this region shrinks with increasing s, so that the classical state variables emerge as envelopes of the quantum mechanical ones.
Improving real-world skills in people with intellectual disabilities: an immersive virtual reality intervention
Authors: Michalski Stefan Carlo , Gallomarino Nicholas Charles , Szpak Ancret , May Kieran William , Lee Gun , Ellison Caroline , Loetscher Tobias 
Published: April 2023

AbstractVirtual reality (VR) is a promising tool for training life skills in people with intellectual disabilities. However, there is a lack of evidence surrounding the implementation, suitability, and effectiveness of VR training in this population. The present study investigated the effectiveness of VR training for people with intellectual disabilities by assessing (1) their ability to complete basic tasks in VR, (2) real-world transfer and skill generalisation, and (3) the individual characteristics of participants able to benefit from VR training. Thirty-two participants with an intellectual disability of varying severity completed a waste management training intervention in VR that involved sorting 18 items into three bins. Real-world performance was measured at pre-test, post-test, and delayed time points. The number of VR training sessions varied as training ceased when participants met the learning target (≈ 90% correct). A survival analysis assessed training success probability as a function of the number of training sessions with participants split by their level of adaptive functioning (as measured on the Adaptive Behaviour Assessment System Third Edition). The learning target was met by 19 participants (59.4%) within ten sessions (Mdn = 8.5, IQR 4–10). Real-world performance significantly improved from pre- to post-test and pre- to delayed test. There was no significant difference from post- to delayed test. Further, there was a significant positive relationship between adaptive functioning and change in the real-world assessment from the pre-test to the post- and delayed tests. VR facilitated the learning of most participants, which led to demonstrations of real-world transfer and skill generalisation. The present study identified a relationship between adaptive functioning and success in VR training. The survival curve may assist in planning future studies and training programs.
Evaluation of apathy in non-clinical populations: validation, psychometric properties, and normative data of the Italian version of Apathy-Motivation Index (AMI)
Authors: Altieri Manuela , Maggi Gianpaolo , Rippa Valentina , Santangelo Gabriella 
Published: April 2023

Abstract
Introduction
Evaluation of apathy in non-clinical populations is relevant to identify individuals at risk for developing cognitive decline in later stages of life, and it should be performed with questionnaires specifically designed for healthy individuals, such as the Apathy-Motivation Index (AMI); therefore, the aim of the present study was to validate the AMI in a healthy Italian population, and to provide normative data of the scale.

Materials and methods
Data collection was performed using a survey completed by 500 healthy participants; DAS, MMQ-A, BIS-15, PHQ-9, and GAD-7 were used to investigate convergent and divergent validity. Internal consistency and factorial structure were also evaluated. A regression-based procedure and receiver operating characteristics (ROC) analyses were used to evaluate the influence of socio-demographic variables on AMI scores and to provide adjusting factors and three cut-offs for the detection of mild, moderate, and severe apathy.

Results
The Italian version of the AMI included 17 items (one item was removed because it was not internally consistent) and demonstrated good psychometric properties. The three-factor structure of AMI was confirmed. Multiple regression analysis revealed no effect of sociodemographic variables on the total AMI score. ROC analyses revealed three cut-offs of 1.5, 1.66, and 2.06 through the Youden’s J statistic to detect mild, moderate, and severe apathy, respectively.

Conclusion
The Italian version of the AMI reported similar psychometric properties, factorial structure, and cut-offs to the original scale. This may help researchers and clinicians to identify people at risk and address them in specific interventions to lower their apathy levels.
Micro-computed Tomography-Based Collagen Orientation and Anisotropy Analysis of Rabbit Articular Cartilage
Authors: Ojanen Simo P. , Finnilä Mikko A. J. , Herzog Walter , Saarakkala Simo , Korhonen Rami K. , Rieppo Lassi 
Published: April 2023

AbstractThe collagen network is the highly organized backbone of articular cartilage providing tissue tensile stiffness and restricting proteoglycan bleaching out of the tissue. Osteoarthritis (OA) diminishes proper collagen network adaptation. Our aim was to provide quantitative three-dimensional (3D) information of the cartilage collagen network adaptation in early osteoarthritis using high resolution micro-computed tomography (µCT)-imaging. Osteochondral samples from the femoral condyles were collected from healthy (N = 8, both legs) and experimental OA rabbit model with anterior cruciate ligament transection (N = 14, single leg). Samples were processed for cartilage µCT-imaging and histological evaluation with polarized light microscopy (PLM). Structure tensor analysis was used to analyse the collagen fibre orientation and anisotropy of the µCT-images, and PLM was used as a validation for structural changes. Depth-wise comparison of collagen fibre orientation acquired with µCT-imaging and PLM correlated well, but the values obtained with PLM were systematically greater than those measured with µCT-imaging. Structure tensor analysis allowed for 3D quantification of collagen network anisotropy. Finally, µCT-imaging revealed only minor differences between the control and experimental groups.
The relationships between the physical and chemical properties of an aquatic environment and the floristic specificity of pleustonic communities in northern Poland
Authors: Kłosowski Stanisław , Pawlikowski Paweł , Jabłońska Ewa , Podgórska Monika 
Published: April 2023

AbstractA comparative phytosociological and habitat analysis of 84 pleustonic phytocoenoses in northern Poland was carried out in order to determine the scale of their floristic distinctiveness and to obtain an answer to the question whether and to what extent the floristic differentiation of pleustonic communities corresponds to the differentiation of their habitat conditions. Based on phytosociological studies, it was shown that the investigated phytocoenoses are not random groups of species, but well differentiated in terms of floristic composition and phytocoenotic structure by communities. It was shown that the studied phytocoenoses represent the following separate associations in phytosociological terms:Salvinio natantis-Spirodeletum polyrhizae, Lemno-Spirodeletum polyrhizae, Riccietum fluitantisandRicciocarpetum natantis.Hydrochemical studies showed that the floristic distinctiveness of these communities is largely confirmed by the differentiation of properties of the water habitat.Salvinio natantis-Spirodeletum polyrhizaeis characterised by the deepest waters (mainly 0.7–1.2 m), alkaline, of a low colour, rich in ions (Mg2+, Na+, Cl−) and therefore characterised by the highest electrolytic conductivity, poor in dissolved organic matter, NO3−and total iron.Lemno-Spirodeletum polyrhizaeis characterised by medium deep waters (mainly 0.3–0.8 m), mostly alkaline, of a low colour, less rich in ions (Ca2+, Na+, Cl−) and relatively low in dissolved organic matter and NO3−.Riccietum fluitantisis characterised by shallow waters (mainly 0.2–0.4 m), most often slightly acidic, of a quite high colour, low in cations and Cl−, and relatively rich in total iron, NO3−, and dissolved organic matter.Ricciocarpetum natantisis characterised by the shallowest waters, (mainly < 0.3 m), most often acidic, of the highest colour, low in ions, and rich in total iron, dissolved silica, NO3−and dissolved organic matter. By demonstrating habitat distinctiveness, the studied pleustonic communities may have significance as indicators of various types of aquatic environment.
Geodesics on a K3 surface near the orbifold limit
Authors: Lye Jørgen Olsen 
Published: April 2023

AbstractThis article studies Kummer K3 surfaces close to the orbifold limit. We improve upon estimates for the Calabi–Yau metrics due to Kobayashi. As an application, we study stable closed geodesics. We use the metric estimates to show how there are generally restrictions on the existence of such geodesics. We also show how there can exist stable, closed geodesics in some highly symmetric circumstances due to hyperkähler identities.
Hypergeometric structures in Feynman integrals
Authors: Blümlein J. , Saragnese M. , Schneider C. 
Published: April 2023

AbstractFor the precision calculations in perturbative Quantum Chromodynamics (QCD) gigantic expressions (several GB in size) in terms of highly complicated divergent multi-loop Feynman integrals have to be calculated analytically to compact expressions in terms of special functions and constants. In this article we derive new symbolic tools to gain large-scale computer understanding in QCD. Here we exploit the fact that hypergeometric structures in single and multiscale Feynman integrals emerge in a wide class of topologies. Using integration-by-parts relations, associated master or scalar integrals have to be calculated. For this purpose it appears useful to devise an automated method which recognizes the respective (partial) differential equations related to the corresponding higher transcendental functions. We solve these equations through associated recursions of the expansion coefficient of the multivalued formal Taylor series. The expansion coefficients can be determined using either the package in the case of linear difference equations or by applying heuristic methods in the case of partial linear difference equations. In the present context a new type of sums occurs, the Hurwitz harmonic sums, and generalized versions of them. The code transforming classes of differential equations into analytic series expansions is described. Also partial difference equations having rational solutions and rational function solutions of Pochhammer symbols are considered, for which the code is designed. Generalized hypergeometric functions, Appell-, Kampé de Fériet-, Horn-, Lauricella-Saran-, Srivasta-, and Exton–type functions are considered. We illustrate the algorithms by examples.
Knapsack problems with position-dependent item weights or profits
Authors: Gawiejnowicz Stanisław , Halman Nir , Kellerer Hans 
Published: April 2023

AbstractWe consider three new knapsack problems with variable weights or profits of items, where the weight or profit of an item depends on the position of the item in the sequence of items packed in the knapsack. We show how to solve the problems exactly using dynamic programming algorithms with pseudo-polynomial running times and propose fully polynomial-time approximation schemes for their approximate solution.
Stochastic Volterra equations with time-changed Lévy noise and maximum principles
Authors: di Nunno Giulia , Giordano Michele 
Published: April 2023

AbstractMotivated by a problem of optimal harvesting of natural resources, we study a control problem for Volterra type dynamics driven by time-changed Lévy noises, which are in general not Markovian. To exploit the nature of the noise, we make use of different kind of information flows within a maximum principle approach. For this we work with backward stochastic differential equations (BSDE) with time-change and exploit the non-anticipating stochastic derivative introduced in Di Nunno and Eide (Stoch Anal Appl 28:54-85, 2009). We prove both a sufficient and necessary stochastic maximum principle.
Considerations for modelling diffuse high-grade gliomas and developing clinically relevant therapies
Authors: Higginbottom Sarah L. , Tomaskovic-Crook Eva , Crook Jeremy M. 
Published: April 2023

AbstractDiffuse high-grade
gliomas contain some of the most dangerous human cancers that lack curative treatment options. The recent molecular stratification of gliomas by the World Health Organisation in 2021 is expected to improve outcomes for patients in neuro-oncology through the development of treatments targeted to specific tumour types. Despite this promise, research is hindered by the lack of preclinical modelling platforms capable of recapitulating the heterogeneity and cellular phenotypes of tumours residing in their native human brain microenvironment. The microenvironment provides cues to subsets of glioma cells that influence proliferation, survival, and gene expression, thus altering susceptibility to therapeutic intervention. As such, conventional in vitro cellular models poorly reflect the varied responses to chemotherapy and radiotherapy seen in these diverse cellular states that differ in transcriptional profile and differentiation status. In an effort to improve the relevance of traditional modelling platforms, recent attention has focused on human pluripotent stem cell-based and tissue engineering techniques, such as three-dimensional (3D) bioprinting and microfluidic devices. The proper application of these exciting new technologies with consideration of tumour heterogeneity and microenvironmental interactions holds potential to develop more applicable models and clinically relevant therapies. In doing so, we will have a better chance of translating preclinical research findings to patient populations, thereby addressing the current derisory oncology clinical trial success rate.
Flame-retardant hybrid composite manufacturing through reinforcing lignocellulosic and carbon fibers reinforced with epoxy resin (F@LC)
Authors: Hasan K. M. Faridul , Horváth Péter György , Kóczán Zsófia , Bak Miklós , Bejó László , Alpár Tibor 
Published: April 2023

AbstractNovel flame retardant hybrid composites were developed from lignocellulosic and carbon fibers reinforced with epoxy resin using hot pressing technology. The size of the lignocellulosic fibers was within 0.045 to 0.8 mm, and the carbon fibers ranged from 5 to 8 mm. The nominal thickness of the composites was 10 mm, whereas the nominal density was 730 kg/m3. The composite dimensions were 400 × 400 mm2. The developed panels were tested for internal bonding strength and flexural properties to investigate their mechanical performance. Furthermore, SEM (Scanning electron microscopy) test was conducted to examine the morphologies of the products before and after fracture and found substantial quantities of both types of fiber in the composite system. The EDX (Energy disruptive X-ray) analysis also displayed the chemical elements present in the developed products. Moreover, an FTIR (Fourier transform infrared spectroscopy) study showed strong chemical interactions among the lignocellulosic and carbon fibers with the thermosetting epoxy polymers. The flame retardancy tests of the composite materials also showed significant thermal stability, especially after loading carbon fibers in the composite system. Moreover, dimensional stability showed an improving trend with the increase of carbon fibers as the reinforcement. Overall, the composite materials developed using lignocellulosic and carbon fibers with epoxy resin are showing a novel route to develop composites with high mechanical performance and considerable flame retardancy.Graphical abstract