bluuebunny/crossref_metadata_2025_split huggingface dataset:
New records of Ripersiella (Tinsley) (Hemiptera: Coccomorpha: Rhizoecidae) species and identification key of Rhizoecidae in Italy
Authors: Mazzeo Gaetana , Ricupero Michele , Campo Giuseppe , Conti Filadelfo , Russo Agatino 
Published: September 2023

AbstractBiological invasions are one of the major constraints worldwide because of the economic and environmental consequences they may pose. Root mealybugs (Hemiptera: Coccomorpha: Rhizoecidae) are continuously transported worldwide with plant soil because of their cryptic behavior. In this study it was reported the presence of Ripersiella multiporifera Jansen in Sicily for the first time and discussed the presence of R. maasbachi (Jansen) and R. hibisci (Kawai & Takagi) in Italy. A key is provided to identify the species of Rhizoecidae currently known in Italy. The species were identified by morphological features and characterized molecularly by using a partial COI mitochondrial gene. Our report alerts the presence of alien root mealybugs in Italy. R. hibisci is a quarantine species listed in Annex IIA of EU Regulation 2019/2072.
Driving Decision Making of Autonomous Vehicle According to Queensland Overtaking Traffic Rules
Authors: Bhuiyan Hanif , Governatori Guido , Rakotonirainy Andry , Wong Meng Weng , Mahajan Avishkar 
Published: September 2023

AbstractImproving the safety of autonomous vehicles (AVs) by making driving decisions in accordance with traffic rules is a complex task. Traffic rules are often expressed in a way that allows for interpretation and exceptions, making it difficult for AVs to follow them. This paper proposes a novel methodology for driving decision making in AVs based on defeasible deontic logic (DDL). We use DDL to formalize traffic rules and facilitate automated reasoning, allowing for the effective handling of rule exceptions and the resolution of vague terms in rules. To supplement the information provided by traffic rules, we incorporate an ontology for AV driving behaviour and environment information. By applying automated reasoning to formalized traffic rules and ontology-based AV driving information, our methodology enables AVs to make driving decisions in accordance with traffic rules. We present a case study focussing on the overtaking traffic rule to illustrate the usefulness of our methodology. Our evaluation demonstrates the effectiveness of the proposed driving decision-making methodology, highlighting its potential to improve the safety of AVs on the road.
Limpopo National Park (Mozambico): groundwater assessment as a tool for a sustainable management of the area
Authors: Sappa G. , Vitale S. , Ferranti F. , Barbieri M. 
Published: September 2023

AbstractThis paper deals with updated results coming from hydrogeological studies carried on the framework of the SECOSUD Phase II, called “Conservation and equitable use of biological diversity in the SADC region (Southern African Development Community), a project supported by the Italian Ministry of Foreign Affairs in the SADC, whose focus area includes South Africa Development Countries. The main goal of the SECOSUD Phase II Project is the definition and implementation of scenarios for sustainable development, aimed at an equitable conservation of biodiversity resources and, as a consequence of this target, the hydrogeological characterization, with the groundwater recharge assessment, of this area and its buffer zone. Limpopo National Park is one of the jewels in the crown of Mozambique’s protected areas. As a matter of fact, sustaining the conservation of biodiversity, due to its complexity and multiple drivers, which stress it, is on first a matter of water environment assessment, as most ecosystems are highly dependent on the hydrological cycle and groundwater availability. After gathering regional and local geological data, which let us set up a detailed geological map of the area under study, pointing out the main outcropping geological units, with their main hydrogeological properties, the methodological approach adopted has been to assess the potential infiltration, applying the Inverse Hydrogeological Budget Technique, performed for the focus area. Because of the lack of meteorological data referred to Limpopo National Park, it has been applied a spatial distribution of precipitation measurements, collected in many gauge stations, located in the Kruger National Park during the last 54 years, which represent an interesting rainfall historical series. The target of the study has been to assess a trend of meteorological data with the aim of understanding how precipitations could affect groundwater recharge, and their influence on groundwater availability. The estimation of groundwater recharge is the tool for suggesting better water management in the area, aimed to preserve as much biodiversity as people living in the buffer zone.
3D Point Cloud Semantic Segmentation Through Functional Data Analysis
Authors: Oviedo de la Fuente Manuel , Cabo Carlos , Roca-Pardiñas Javier , Loudermilk E. Louise , Ordóñez Celestino 
Published: September 2023

AbstractHere, we propose a method for the semantic segmentation of 3D point clouds based on functional data analysis. For each point of a training set, a number of handcrafted features representing the local geometry around it are calculated at different scales, that is, varying the spatial extension of the local analysis. Calculating the scales at small intervals allows each feature to be accurately approximated using a smooth function and, for the problem of semantic segmentation, to be tackled using functional data analysis. We also present a step-wise method to select the optimal features to include in the model based on the calculation of the distance correlation between each feature and the response variable. The algorithm showed promising results when applied to simulated data. When applied to the semantic segmentation of a point cloud of a forested plot, the results proved better than when using a standard multiscale semantic segmentation method. The comparison with two popular deep learning models showed that our proposal requires smaller training samples sizes and that it can compete with these methods in terms of prediction.
Puerarin alleviates sleep disorders in aged mice related to repairing intestinal mucosal barrier
Authors: Tao Qing , Zhang Jinhua , liang Qiao , Song Shiyu , Wang Shuxia , Yao Xiaoming , Gao Qian , Wang Lei 
Published: September 2023

AbstractMore and more evidence suggests that puerarin, a potential remedy for gut inflammation, may have an ameliorative effect on sleep disturbances. However, the relationship between puerarin and sleep disruption has not been extensively researched. This study aims to explore the role and mechanisms of puerarin in improving sleep disorders. We established a light-induced sleep disorder model in mice and assessed the effects of puerarin on cognitive behavior using open field and water maze tests. Pathological detection demonstrated that sleep disturbances resulted in observable damage to the liver, lung, and kidney. Puerarin reversed multi-organ damage and inflammation. Further, puerarin activated paneth cells, resulting in increased lysozyme and TGF-β production, and stimulating intestinal stem cell proliferation. Puerarin also effectively inhibited the expression of F4/80, iNOS, TNF-α, and IL-1β in the small intestine, while it increased Chil3, CD206, and Arg-1 levels. Moreover, puerarin treatment significantly decreased P-P65, TLR4, Bcl-xl, and cleaved caspase-3 protein levels while increasing barrier protein levels, including ZO-1, Occludin, Claudin 1 and E-cadherin suggesting a reduction in inflammation and apoptosis in the gut. Overall, puerarin diminished systemic inflammation, particularly intestinal inflammation, and enhanced intestinal barrier integrity in mice with sleep disorders. Our findings suggest a potential new therapeutic pathway for sleep disorders.
Graphical Abstract
Stability analysis of loose accumulation slopes under rainfall: case study of a high-speed railway in Southwest China
Authors: Wang Xin , Su Qian , Zhang Zongyu , Huang Feihu , He Chenfang 
Published: September 2023

AbstractThe high and steep slopes along a high-speed railway in the mountainous area of Southwest China are mostly composed of loose accumulations of debris with large internal pores and poor stability, which can easily induce adverse geological disasters under rainfall conditions. To ensure the smooth construction of the high-speed railway and the subsequent safe operation, it is necessary to master the stability evolution process of the loose accumulation slope under rainfall. This article simulates rainfall using the finite element analysis software’s hydromechanical coupling module. The slope stability under various rainfall situations is calculated and analysed based on the strength reduction method. To validate the simulation results, a field monitoring system is established to study the deformation characteristics of the slope under rainfall. The results show that rainfall duration is the key factor affecting slope stability. Given a constant amount of rainfall, the stability of the slope decreases with increasing duration of rainfall. Moreover, when the amount and duration of rainfall are constant, continuous rainfall has a greater impact on slope stability than intermittent rainfall. The setting of the field retaining structures has a significant role in improving slope stability. The field monitoring data show that the slope is in the initial deformation stage and has good stability, which verifies the rationality of the numerical simulation method. The research results can provide some references for understanding the influence of rainfall on the stability of loose accumulation slopes along high-speed railways and establishing a monitoring system.
Hesitant Fermatean fuzzy Bonferroni mean operators for multi-attribute decision-making
Authors: Wang Yibo , Ma Xiuqin , Qin Hongwu , Sun Huanling , Wei Weiyi 
Published: September 2023

AbstractHesitant Fermatean fuzzy sets (HFFS) can characterize the membership degree (MD) and non-membership degree (NMD) of hesitant fuzzy elements in a broader range, which offers superior fuzzy data processing capabilities for addressing complex uncertainty issues. In this research, first, we present the definition of the hesitant Fermatean fuzzy Bonferroni mean operator (HFFBM). Further, with the basic operations of HFFS in Einstein t-norms, the definition and derivation process of the hesitant Fermatean fuzzy Einstein Bonferroni mean operator (HFFEBM) are given. In addition, considering how weights affect decision-making outcomes, the hesitant Fermatean fuzzy weighted Bonferroni mean (HFFWBM) operator and the hesitant Fermatean fuzzy Einstein weighted Bonferroni mean operator (HFFEWBM) are developed. Then, the properties of the operators are discussed. Based on HFFWBM and HFFEWBM operator, a new multi-attribute decision-making (MADM) approach is provided. Finally, we apply the proposed decision-making approach to the case of a depression diagnostic evaluation for three depressed patients. The three patients' diagnosis results confirmed the proposed method's validity and rationality. Through a series of comparative experiments and analyses, the proposed MADM method is an efficient solution for decision-making issues in the hesitant Fermatean fuzzy environment.
Efficient Network Representation Learning via Cluster Similarity
Authors: Fujiwara Yasuhiro , Ida Yasutoshi , Kumagai Atsutoshi , Nakano Masahiro , Kimura Akisato , Ueda Naonori 
Published: September 2023

AbstractNetwork representation learning is a de facto tool for graph analytics. The mainstream of the previous approaches is to factorize the proximity matrix between nodes. However, if n is the number of nodes, since the size of the proximity matrix is $$n \times n$$

n
×
n

, it needs $$O(n^3)$$

O
(

n
3

)

time and $$O(n^2)$$

O
(

n
2

)

space to perform network representation learning; they are significantly high for large-scale graphs. This paper introduces the novel idea of using similarities between clusters instead of proximities between nodes; the proposed approach computes the representations of the clusters from similarities between clusters and computes the representations of nodes by referring to them. If l is the number of clusters, since $$l \ll n$$

l
≪
n

, we can efficiently obtain the representations of clusters from a small $$l \times l$$

l
×
l

similarity matrix. Furthermore, since nodes in each cluster share similar structural properties, we can effectively compute the representation vectors of nodes. Experiments show that our approach can perform network representation learning more efficiently and effectively than existing approaches.
An Application of the Analytic Hierarchy Process to the Evaluation of Companies’ Data Maturity
Authors: Malacaria Simone , De Mauro Andrea , Greco Marco , Grimaldi Michele 
Published: September 2023

AbstractThe aim of this study is to evaluate data maturity of a sample of Italian firms of different sectors and sizes, obtained through an online assessment submitted to 261 professionals and entrepreneurs operating in the data/IT domain. The paper's objective is to assess the relative importance of the factors that determine the success of big data initiatives, according to the company structure and managerial perspective. The questionnaire was digitally submitted to IT professionals and decision-makers in Italy through the LinkedIn platform. The assessment was divided into two sections: the first focused on the assessment of 8 critical success factors for big data, whereas the second assigned weights based on an application of the analytic hierarchy process. The result of this process is a weighted-scores system that reflects the relative importance that managers and employees give to different domains. Respondents agreed to the importance of integrated architecture, data-friendly corporate culture, and integrated organization domains. Once the results consider the weights from the AHP, data friendliness becomes the most sought-after characteristic. The findings provide direction for further development of this assessment system.
An analysis approach for building collapse accident using system thinking approach and SEA model
Authors: He Yu-Ting , Atangana Njock Pierre Guy 
Published: September 2023

AbstractThe frequent occurrence of building collapse accidents not only causes significant casualties, but also jeopardizes local economies. This paper adopts a combinatory assessment approach to showcase the lessons learned from a recent building collapse in Changsha, China. The proposed approach blends the system thinking approach and strategic environmental assessment (SEA) model. It delineates the causes of collapse and provide key leverage points for safety management. The results show that the primary causes for the collapse are the poor construction quality, illegal alterations, and lack of regulations enforcement. The management of rural housing construction in Hunan Province achieved a total score of 4 out of 30. It was also determined that the key prevention measures for abating these deleterious phenomena involve ensuring quality assurance/quality control, efficiently assessing safety risk, and timely performing structural health monitoring. This study is bound to enhance the understanding of collapse accidents and foster the achievement of sustainable cities and communities.
The ethical challenges of diversifying genomic data: A qualitative evidence synthesis
Authors: Hardcastle Faranak , Lyle Kate , Horton Rachel , Samuel Gabrielle , Weller Susie , Ballard Lisa , Thompson Rachel , De Paula Trindade Luiz Valerio , Gómez Urrego José David , Kochin Daniel , Johnson Tess , Tatz-Wieder Nechama , Redrup Hill Elizabeth , Robinson Adams Florence , Eskandar Yoseph , Harriss Eli , Tsosie Krystal S. , Dixon Padraig , Mackintosh Maxine , Nightingale Lyra , Lucassen Anneke 
Published: September 2023

Abstract
This article aims to explore the ethical issues arising from attempts to diversify genomic data and include individuals from underserved groups in studies exploring the relationship between genomics and health. We employed a qualitative synthesis design, combining data from three sources: 1) a rapid review of empirical articles published between 2000 and 2022 with a primary or secondary focus on diversifying genomic data, or the inclusion of underserved groups and ethical issues arising from this, 2) an expert workshop and 3) a narrative review. Using these three sources we found that ethical issues are interconnected across structural factors and research practices. Structural issues include failing to engage with the politics of knowledge production, existing inequities, and their effects on how harms and benefits of genomics are distributed. Issues related to research practices include a lack of reflexivity, exploitative dynamics and the failure to prioritise meaningful co-production. Ethical issues arise from both the structure and the practice of research, which can inhibit researcher and participant opportunities to diversify data in an ethical way. Diverse data are not ethical in and of themselves, and without being attentive to the social, historical and political contexts that shape the lives of potential participants, endeavours to diversify genomic data run the risk of worsening existing inequities. Efforts to construct more representative genomic datasets need to develop ethical approaches that are situated within wider attempts to make the enterprise of genomics more equitable.
Technical conferences as a technique of internationalism
Authors: Reinisch Jessica 
Published: September 2023

AbstractThis paper looks at a genre of meetings that, while neither purely ‘scientific’ nor ‘diplomatic’, drew on elements from both professional spheres and gained prominence in the interwar decades and during the Second World War. It proposes to make sense of ‘technical conferences’ as a phenomenon that was made by and through scientific experts and politicians championing the organizing power of rationality, science and liberal internationalism. Against the background of swelling ranks of state-employed scientists, this paper documents the emergence of technical conferences as the forums where they got down to work. To make this case the paper traces the influence of a new way of thinking about the function and organization of conferences, originating in the time around the First World War, on one international organization in particular: the United Nations Relief and Rehabilitation Administration (UNRRA), as a new hub of scientists and technicians.
Transitioning to sustainable academic conferences needs more experimentation and reflection
Authors: Raven Rob , Hadfield Paris , Butler Brianna , Eagleton Jennifer , Giraud Gael , Jacob Merin , Markard Jochen , Schiller Katharina , Swilling Mark , Tshangela Mapula 
Published: September 2023

Non-technical summary
Accelerated decarbonization of academic conferences is necessary and urgent. Despite the window of opportunity that COVID-19 created for rethinking conferences, there is a risk of slipping back into old habits now that restrictions are lifted. This commentary reports on recent experiences with a unique, sustainable approach to academic conferencing involving an international partnership and hub model across three continents. There is a need to continue to experiment with and implement new modes of sustainable academic conferencing.

Technical summary
In response to increasing demands to move away from carbon-intensive academic conferences, and a need to address social justice issues, the author-team designed, implemented, and experimented with a new conference model. Three key-design choices informed the model. First, instead of the common single-host-single-location approach, we established a partnership between three universities across three continents. Second, we adopted a hub model of three online conference days, followed by three non-hybrid, in-person only conference days. Third, we sought to accommodate global participation by organizing each of the online conference days during daylight hours in the respective time zones. We find that the model promotes less air travel and improved global south participation. Our approach adds to a growing number of experiments with new modes of academic conferencing in a world that is facing climate and inequality crises.

Social media summary
Decarbonizing academic conferences is necessary and urgent. This commentary reveals experiences with a hub-based format.
Moho Inversion by Gravity Anomalies in the South China Sea: Updates and Improved Iteration of the Parker‐Oldenburg Algorithm
Authors: Rao Weibo , Yu Nan , Chen Gang , Xu Xinyu , Zhao Simin , Song Zhaoqi , Liu Jiazheng , Wan Longtu , Hu Changhong 
Published: September 2023

AbstractThe Moho is the interface between crust and mantle, and accurate location of the Moho is important for both resource exploration and deep earth condition and structural change investigations. The theory of the traditional Parker‐Oldenburg (P‐O) method is quite simple and it is widely applied in the frequency domain of Moho depth inversion. However, Moho fluctuation simulations using the P‐O method are not reliable because of the lack of field geographic data constraints during the inversion process and the excessively smoothing of data details caused by using filters to correct the source data signals. To solve those problems, we propose an improved iteration P‐O method with a variable density contrast model, the iterative process is constrained by geological data in the inversion parameters, and the variable depth of the gravity interface is iterated using an equivalent form of upward continuation in the Fourier domain, which is more stable and convergent than downward continuation term in original P‐O method. Synthetic experiments indicate that improved method has the better consistency among the simulations than original method, and our improved method has the smallest root mean square (RMS) of 0.59 km. In a real case, we employed the improved method to invert for the Moho depth of the South China Sea (SCS), and the RMS between our Moho depth model and the seismological data is the smallest value of 2.27 km. The synthetic experiments and application of the model to the SCS further prove that our method is practical and efficient.