bluuebunny/crossref_metadata_2025_split huggingface dataset:
Convergence analysis of Picard–SP iteration process for generalized $$\alpha $$–nonexpansive mappings
Authors: Nawaz Bashir , Ullah Kifayat , Gdawiec Krzysztof 
Published: June 2024

AbstractIn this manuscript, we introduce a novel hybrid iteration process called the Picard–SP iteration process. We apply this new iteration process to approximate fixed points of generalized $$\alpha $$
α
–nonexpansive mappings. Convergence analysis of our newly proposed iteration process is discussed in the setting of uniformly convex Banach spaces and results are correlated with some other existing iteration processes. The dominance of the newly proposed iteration process is exhibited with the help of a new numerical example. In the end, the comparison of polynomiographs generated by other well-known iteration processes with our proposed iteration process has been presented to make a strong impression of our proposed iteration process.
Internet traffic prediction analog to solitons propagation in optical fibers via the concatenation model and stability analysis
Authors: Abdel-Gawad Hamdy I. , Abdel-Gawad Ahmed H. 
Published: June 2024

AbstractInternet traffic (IT) is a measure of data transfer across devices. In this paper, an analogy is made between data transfer and soliton propagation in optical fibers. This is achieved by employing the concatenation model (CM) that describes soliton propagation in optical fibers, which is presented recently in the literature. The CM contains nonlinear space-time dispersion effect, that may lead to bottleneck soliton shape (BNSS). Thus, in view of this model, BNSS effect of soliton propagation may occur, which is analogous to a possible BN in IT. So, the prediction of the characteristics of internet traffic can be depicted via the CM, which is studied here with Caputo-q time derivative. Also, a variety of exact solutions of the CM are derived. These solutions are represented graphically and they show multiple shapes of concatenated solitons. Among them, bottleneck, M-shaped, hybrid M shaped, chirped solitons and vector of dromian patterns. On the other side, the speed of IT and chips heating are estimated. It is found that the speed of IT is constant with time and the effects of distributed time delay (recent memory (RM)) is to slow the traffic speed. This is done via varying the fractional order. Also, it is observed, when accounting for RM, that the chip heating is too small. We think that the results for the speed of IT and chip heat are, qualitatively, realistic. The stability of a steady state solution is analyzed and the controlled parameters for stability is determined.
Testing a theory of strategic multi-product choice
Authors: Fox Edward J. , Pulgar Hristina , Semple John H. 
Published: June 2024

AbstractThis paper tests a theory of strategic multi-product choice (SMPC) using empirical evidence from a large-scale choice experiment, two smaller longitudinal choice experiments, and multi-market panel data. Multi-product choice involves two stages. In the first stage, the consumer chooses a set of substitutable products, where “set” refers to both the variety of alternatives and the quantities of each. In the second stage, the set is consumed. Assuming consumers are strategic, their consumption decisions will consider both the utility of whichever product is selected for consumption and the expected utility (i.e., value) of the set that remains. SMPC therefore requires a dynamic model. We test two such dynamic models in this paper. These models are derived from a basic random utility framework with a stochastic error term for the utility of each product alternative at the moment of consumption. Despite maintaining state variables for the quantity of every alternative, these SMPC dynamic models offer both a value function and optimal consumption policy in closed form. These structures allow us to test for strategic consumption in the second stage and for optimality of the choice sets selected in the first stage. Data from the large-scale choice experiment and the smaller longitudinal choice experiments support strategic consumer decision-making, consistent with SMPC theory. SMPC theory further predicts that the amount of variety consumers select will be higher for lower consumption rates and lower for higher consumption rates. Evidence from panel data of yogurt purchases supports this prediction. While we find that consumption choices are consistent with SMPC theory, they are not consistent with alternative explanations such as variety seeking or diversification bias. Viewed in its entirety, the empirical evidence presented in this paper confirms that both the choice set selected and the way it is consumed are consistent with dynamic models of future preference uncertainty.
The Figure of the Unknown within Sacco’s Theory
Authors: Heritier Paolo 
Published: June 2024

AbstractThe article analyzes one aspect of Rodolfo Sacco’s complex and innovative theoretical itinerary as it evolved. While the author’s theoretical perspective is often remembered as the theory of the legal formant and of the mute origin of law within a comparatist perspective, it seems to me that another area of his work remains relevant and needs to be explored further, perhaps beyond the very methodological ways provided by the author. From the work on interpretation to the legal anthropology, the implicit copresence of mute and spoken represents one of the most interesting features of the theory, which appears capable of intercepting many contemporary problems of the evolutions of the law. The paper will move toward a different direction: with the aim to show how there are very different theoretical positions within the philosophy of law that can be approached from the perspective of comparative law in the formulation proposed by Rodolfo Sacco, around the central problem of the radical transformations of the concept of law. Thus, a problem is identified, at once epistemological and semiotic, that appears central to the configuration of legal thought in the age of globalization: the epistemological role of the unknown in the construction of knowledge, as a modular methodological problem and its implicit Vichian ancestry.
Herpesviruses in migrating procellariforms, northeastern Brazil
Authors: Sacristán Carlos , Duarte-Benvenuto Aricia , Navas-Suárez Pedro Enrique , Zamana-Ramblas Roberta , Baes Laura , Codeas Barbara Sophia , Pavanelli Larissa , Ikeda Joana , Catão-Dias José Luiz , Ewbank Ana Carolina 
Published: June 2024

AbstractSeabirds are one of the most threatened avian groups. Viruses, including herpesvirus, represent considerable threats to marine avifauna. Herein, our goal was to survey herpesvirus in Procellariiformes that stranded in Brazil between June and July 2021. We analyzed 12 Cory's shearwaters (Calonectris borealis), two Great Shearwaters (Ardenna gravis, syn. Puffinus gravis) and one Yellow-nosed Albatross (Thalassarche chlororynchos) found in an unusual mortality event in Bahía state, northeastern Brazil. After necropsy, selected tissue samples were tested for herpesvirus using a broad-range nested PCR. Overall, 20% (3/15) of the birds were herpesvirus-positive, i.e., two Cory's Shearwaters and one Great Shearwater. One alphaherpesvirus sequence type was identified in each shearwater species, classified into the genus Mardivirus. This study describes two likely novel herpesviruses in shearwaters, contributing to the currently very scarce data regarding infectious agents in Procellariiformes. Further studies are necessary to evaluate the presence and characteristics of herpesvirus in Procellariiformes, and the presence (or not) of related disease in order to understand the epidemiology of this infectious agent and eventually contribute to the conservation of this endangered seabird group.
Influencing factors of delay in seeking medical attention of patients with obstructive sleep apnea based on the Model of Pathways to Treatment in China: a qualitative analysis
Authors: Shang Hongyan , Chen Dandan , Deng Qingmei , Ma Zuchang 
Published: June 2024

Abstract
Background
There is the highest estimated number of patients with obstructive sleep apnea (OSA) in China. Early treatment could lead to fewer complications associated with OSA. This study aimed to analyze the factors influencing help-seeking from the first symptom discovery to treatment in OSA.

Methods
Semi-structured interview outline was designed to conduct face-to-face interview based on the analyses of a great number of related literatures on the delay in seeking medical attention of patients with OSA. 15 patients diagnosed were interviewed between June 2021 to September 2022 in general hospital of Shenyang, Northeastern of China. Qualitative data was analyzed by content analysis using the Model of Pathways to Treatment.

Results
Analyses identified factors contributing to elapsed time from first symptom discovery to received treatment that are linked to disease characteristic, patients, health system organization. Appraisal interval is most obvious for patients with OSA, but it is difficult to pinpoint precisely because the patients didn’t remember exactly when the first symptom was detected.

Conclusions
Patients diagnosed with OSA didn’t initially interpret the snore as a warning sign and even thought it was a blessing. The findings provided guidance or avenues for reducing elapsed time between the first symptom and received treatment.
Hydrodynamics and water quality of a highly anthropized wetland: the case study of the Massaciuccoli basin (Tuscany, Italy)
Authors: Pasquetti Francesca , Natali Stefano , Luppichini Marco , Bini Monica , Del Seppia Nicola , Delgado-Huertas Antonio , Giannecchini Roberto 
Published: June 2024

AbstractOwing to increasing anthropogenic impacts, wetlands have suffered a serious environmental decline in recent decades. The sustainable management of these natural resources is fundamental to maintain both the ecosystems and the economic activities. The Lake Massaciuccoli and nearby areas represent one of the largest residual coastal marshy areas in Tuscany (Italy). This wetland is characterized by large-scale and intensive agricultural use and affected by reclamation activities, with consequent problems of erosion, subsidence and lake eutrophication and siltation. In this context, an integrated study combining hydrochemical data (water levels, electrical conductivity, pH, turbidity, major ions, trace metals) and stable isotopes (H, O, S) has been performed in the southernmost part of the basin, to better disentangle processes and interactions between groundwater and surface water and to understand the origin of solutes and their evolution. Our results indicated that both groundwater and surface water have a meteoric origin and that geochemical composition of groundwater is mainly affected by local geological and biological processes. Moreover, surface water is affected by sea water mixing and evapotranspiration/precipitation processes. The impact of agricultural activity and the use of fertilizers on the water quality appears to be limited as regards nitrates, indicating that less intense agricultural practices implemented in recent years have been successful. As regards sulfates, Fe, and Mn, we cannot fully elucidate the mechanisms underlying human influence, but the oscillation of water level and degradation of peat enhanced by reclamation and agriculture activities likely played an important role in controlling the fate of these elements. Overall, these results underline the importance of integrated approaches to disentangle geochemical processes and will be useful in supporting policy implementation and environmental protection in this valuable area of Tuscany. Findings from this work suggest the need for policy-making authorities to take actions as soon as possible to mitigate risks. Closer co-operation is essential between authorities and farmers to reduce inputs of fertilizers and chemicals into the lake and the surrounding area. Also, additional policy measures should be enforced to reduce the mechanical soil tillage and limit erosion and runoff, such as the NBSs implemented within the Phusicos Project.
Marine macro-litter mass outweighs biomass in trawl catches along abyssal seafloors of Sardinia channel (Italy)
Authors: Carreras-Colom Ester , Follesa Maria Cristina , Carugati Laura , Mulas Antonello , Bellodi Andrea , Cau Alessandro 
Published: June 2024

AbstractThis study provides new insights onto spatial and temporal trends of seafloor macro-litter in the abyssal seafloor of Sardinian channel, in central western Mediterranean (Italy). Trawl surveys were conducted at depths between 884 and 1528 m, thus focusing on one of the least investigated marine environments. None of the considered sites was litter free, with plastics being numerically dominant (57% of items), followed by metal (11%) and glass (16%). Recorded densities and weight ranged between 49.9 and 499 items km−2 and 1.4 and 1052 kg km−2. In the most contaminated sites, the weight of the litter collected in nets represented up to nine times the biomass of benthic megafauna, and, overall, in 60% of hauls macro-litter mass outweighed the biomass collected. Moreover, we report that megafauna was observed to be more abundant in sites where macro-litter presence was more severe. More studies are needed to elucidate the nature of this correlation, with biota being more abundant in hotspots of accumulation of seafloor macro-litter.
A parametric approach for developing embodied environmental benchmark values for buildings
Authors: Szalay Zsuzsa 
Published: June 2024

Abstract
Purpose
The production and construction of buildings cause significant environmental impacts besides those arising from their operation. Recently, some European countries have started introducing life cycle assessment as a mandatory calculation method for new buildings, and it is foreseen that by 2030 this will be done in every member state, at first without any legal minimum values.

Methods
Extensive databases on the embodied impacts of buildings, which would be needed to support setting the baseline impacts, are still missing. This paper proposes an approach for determining bottom-up reference values. A large building sample is generated describing “technically feasible” new buildings. Instead of analysing a few typical buildings, the main parameters describing a building are determined and the ranges are defined that these parameters typically take. With the variation of these parameters, a large building sample is generated, and the surfaces and built-in material quantities are determined for typical construction solutions to assess environmental performance.

Results and discussion
The method is demonstrated by calculating the reference embodied benchmark values for new residential buildings in Hungary. The results show a baseline embodied Global Warming Potential of 9.5–15.5 kg CO2-eq/m2/yr for single-family houses and 9.1–14.3 kg CO2-eq/m2/yr for multi-family houses.

Conclusions
This method is suitable for estimating the environmental impact of typical new buildings in countries where a large pool of real building data is not yet available.
A dynamic model of wealth segregation
Authors: Vicario Eugenio 
Published: June 2024

AbstractWe propose a dynamic model where the real estate market generates wealth segregation within a town. The model develops on the Schelling’s checkerboard dynamics with one main difference: Agents are fully characterized by their wealth, which changes with the progress of the model dynamics. The driver of the segregation is a positive neighborhood externality such that households’ utility is increasing in the average wealth of the neighbors. The identification of a potential function enables prediction of the long-run limiting behavior of the dynamics: Wealth segregation is an endemic result, unless a perturbation at the individual level is introduced. Public policies that mimic the perturbation can reduce wealth segregation.
Examining metacognitive strategy use in L1 and L2 task-situated writing: effects, transferability, and cross-language facilitation
Authors: Xu Wandong , Zhu Xinhua 
Published: June 2024

AbstractDespite the widely recognized importance of metacognition in language learning, relatively few empirical studies have investigated the role of metacognitive strategies with a cross-linguistic perspective. Drawing on the mixed-method design combining questionnaire and interview data, this study systematically investigated the effects, the transfer potential, and the cross-language facilitation of metacognitive strategies between L1 and L2 contexts. Structural equation modelling (SEM) and multigroup analysis results revealed that metacognitive strategies afforded a more prominent predictive role in English (L2) writing than in Chinese (L1) writing; such strategy use transferred between the two writing contexts, which kept invariant between lower- and higher- L2 proficiency groups and between English and non-English major groups; and there was a cross-language facilitation effect of L1 writing metacognitive strategies on L2 writing performance via the mediation of L2 writing metacognitive strategies. Complementary to the quantitative results, the qualitative interview data was analyzed to provide deep insights into the participating students’ metacognitive strategy use in the two task-situated writing. Findings are extensively discussed to offer theoretical and pedagogical implications in this domain.
Influence of dry density and wetting–drying cycles on the soil–water retention curve of compacted loess: experimental data and modeling
Authors: Yuan Kangze , Ni Wankui , Della Vecchia Gabriele , Lü Xiangfei , Wang Haiman , Nie Yongpeng 
Published: June 2024

AbstractIn this paper, the EC-5 water sensor and the MPS-6 water potential sensor were used to measure water content and suction, respectively, to investigate the evolution of soil–water retention properties of compacted loess samples prepared at different dry densities and subjected to different numbers of wetting–drying cycles. The water retention data were integrated with a detailed microstructural investigation, including morphological analysis (by scanning electron microscopy) and pore size distribution determination (by nuclear magnetic resonance). The microstructural information obtained shed light on the double porosity nature of compacted loess, allowing the identification of the effects of compaction dry density and wetting–drying cycles at both intra- and inter-aggregate levels. The information obtained at the microstructural scale was used to provide a solid physical basis for the development of a simplified version of the water retention model presented in Della Vecchia et al. (Int J Numer Anal Meth Geomech 39: 702–723, 2015). The model, adapted for engineering application to compacted loess, requires only five parameters to capture the water retention properties of samples characterized by different compaction dry densities and subjected to different numbers of wetting–drying cycles. The comparison between numerical simulations and experimental results, both original and from the literature, shows that only one set of parameters is needed to reproduce the effects of dry density variation, while the variation of only one parameter allows the reproduction of the effects of wetting and drying cycles. With respect to the approaches presented in the literature, where ad hoc calibrations are often used to fit density and wetting–drying cycle effects, the model presented here shows a good compromise between simplicity and predictive capabilities, making it suitable for practical engineering applications.
Novel Coumarins Derivatives for A. baumannii Lung Infection Developed by High-Throughput Screening and Reinforcement Learning
Authors: Li Jing , Lu Zhou , Wang Liuchang , Shi Huiqing , Chu Bixin , Qu Yingwei , Ye Zichen , Qu Di 
Published: June 2024

Abstract
With the increasing resistance of Acinetobacter baumannii (A. baumannii) to antibiotics, researchers have turned their attention to the development of new antimicrobial agents. Among them, coumarin-based heterocycles have attracted much attention due to their unique biological activities, especially in the field of antibacterial infection. In this study, a series of coumarin derivatives were synthesized and screened for their bactericidal activities (Ren et al. 2018; Salehian et al. 2021). The inhibitory activities of these compounds on bacterial strains were evaluated, and the related mechanism of the new compounds was explored. Firstly, the MIC values and bacterial growth curves were measured after compound treatment to evaluate the antibacterial activity in vitro. Then, the in vivo antibacterial activities of the new compounds were assessed on A. baumannii-infected mice by determining the mice survival rates, counting bacterial CFU numbers, measuring inflammatory cytokine levels, and histopathology analysis. In addition, the ROS levels in the bacterial cells were measured with DCFH-DA detection kit. Furthermore, the potential target and detailed mechanism of the new compounds during infection disease therapy were predicted and evidenced with molecular docking. After that, ADMET characteristic prediction was completed, and novel, synthesizable, drug-effective molecules were optimized with reinforcement learning study based on the probed compound as a training template. The interaction between the selected structures and target proteins was further evidenced with molecular docking. This series of innovative studies provides important theoretical and experimental data for the development of new anti-A. baumannii infection drugs.
A generic deep learning architecture optimization method for edge device based on start-up latency reduction
Authors: Li Qi , Li Hengyi , Meng Lin 
Published: June 2024

AbstractIn the promising Artificial Intelligence of Things technology, deep learning algorithms are implemented on edge devices to process data locally. However, high-performance deep learning algorithms are accompanied by increased computation and parameter storage costs, leading to difficulties in implementing huge deep learning algorithms on memory and power constrained edge devices, such as smartphones and drones. Thus various compression methods are proposed, such as channel pruning. According to the analysis of low-level operations on edge devices, existing channel pruning methods have limited effect on latency optimization. Due to data processing operations, the pruned residual blocks still result in significant latency, which hinders real-time processing of CNNs on edge devices. Hence, we propose a generic deep learning architecture optimization method to achieve further acceleration on edge devices. The network is optimized in two stages, Global Constraint and Start-up Latency Reduction, and pruning of both channels and residual blocks is achieved. Optimized networks are evaluated on desktop CPU, FPGA, ARM CPU, and PULP platforms. The experimental results show that the latency is reduced by up to 70.40%, which is 13.63% higher than only applying channel pruning and achieving real-time processing in the edge device.