bluuebunny/crossref_metadata_2025_split huggingface dataset:
A process model approach to integrate future climate change into corporate strategies
Authors: Gehrke Janna-Malin , Groth Markus , Seipold Peer 
Published: September 2024

Abstract
To prepare for climate-related risks, a scientifically sound forward-looking integration and disclosure of climate-related data is key. Furthermore, companies also face an increasing demand in non-financial reporting, such as the use of climate change scenarios as part of risk analyses as well as for meeting the Technical Screening Criteria for a substantial contribution or Do No Significant Harm (DNSH) to the environmental goals to show alignment of economic activities with the EU Taxonomy Regulation. Currently, however, companies are still leaving notable gaps in the incorporation of forward-looking climate data and scenarios into reporting and long-term planning strategies. Against this background, the paper describes and discusses the development and concept of an eight-step process model as an innovative way to integrate future climate change into corporate processes. This problem-driven approach is developed in close collaboration and co-creation with companies. It comprises the following phases: i) inventory, ii) prioritization, iii) identification, iv) availability, v) enablement, vi) derivation and implementation of measures, vii) evaluation, and viii) process reinforcement. Also taking into account existing regulations, standards and recommendations for risk assessment and reporting, the process model aims to enable decision makers in companies to identify and assess climate change-related impacts and to take regional climate change information into account. Based on this information – combined with additional local knowledge –, companies can identify suitable adaptation options and develop transformative risk-management solutions. This includes new forms of collaboration, embedded in a framework of a transdisciplinary co-production process. Therefore, a close and trust-based cooperation between internal and external stakeholders right from the outset is a key factor for success.
Lateral flow immunoassay for simultaneous detection of C. difficile, MRSA, and K. pneumoniae
Authors: Rubio-Monterde Ana , Rivas Lourdes , Gallegos Marc , Quesada-González Daniel , Merkoçi Arben 
Published: October 2024

AbstractMainly performed within a rapid diagnostic tests company, a lateral flow (LF) system using gold nanoparticles (AuNPs) as transducers is presented able to detect three bacteria of interest, of relevance for antimicrobial resistance (AMR): Clostridioides difficile, methicillin-resistant Staphylococcus aureus (MRSA), and Klebsiella pneumoniae, with a limit of detection of 25 ng/mL of glutamate dehydrogenase (GDH) for C. difficile, 36 ng/mL of penicillin-binding protein 2a (PBP2a) for MRSA, and 4 × 106 CFU/mL for K. pneumoniae. The system showed good results with bacteria culture samples, is user-friendly, and suitable for rapid testing, as the results are obtained within 15 min.
Graphical Abstract
Emerging lasers and light-based therapies in the management of acne: a review
Authors: Jean-Pierre Philippe , Tordjman Lea , Ghodasara Arjun , Nwosu Chika , Nouri Keyvan 
Published: September 2024

Abstract
Acne vulgaris, commonly known as acne, is the most prevalent skin disorder affecting mainly adolescents and young adults, though it can affect people of all ages, making it the most common complaint by patients presenting to a dermatologist. The overactivity of sebaceous glands primarily drives this skin condition due to androgen influence and the presence of Cutibacterium acnes bacteria. Although typically not directly harmful to patient health, acne can be a highly debilitating disease for patients, affecting their self-image and psychosocial well-being. Standard treatments include topical retinoids, benzoyl peroxide, topical antibiotics, and, for more severe cases, systemic antibiotics or isotretinoin, which require prolonged periods of compliance. All these pharmacologic treatments have a risk of side effects ranging from mild ones, like skin irritation and dryness, to severe ones, like depression. Thus, there is a demand for exploring other treatment modalities in treating acne, and laser and light-based therapies have garnered significant interest. This review article will comprehensively assess emerging laser and other light-based therapies that have shown efficacy in treating acne, including the recently FDA-approved 1,726 nm laser.
Comparing EQ-5D-5L, PROPr, SF-6D and TTO utilities in patients with chronic skin diseases
Authors: Szabó Ákos , Brodszky Valentin , Rencz Fanni 
Published: September 2024

Abstract
Objectives
We aim to compare the measurement properties of three indirect (EQ-5D-5L, PROPr, SF-6D) and one direct (time trade-off, TTO) utility assessment methods in patients with chronic skin diseases.

Methods
120 patients with physician-diagnosed chronic skin diseases (psoriasis 39%, atopic dermatitis 27%, acne 19%) completed a cross-sectional survey. Respondents completed the EQ-5D-5L, PROMIS-29+2 and SF-36v1 questionnaires and a 10-year TTO task for own current health. Utilities were computed using the US value sets. Ceiling, convergent and known-group validity were compared across the utilities derived with these four methods. Known-groups were defined based on general, physical and mental health. The agreement between utilities was assessed using intraclass correlation coefficients (ICC).

Results
Mean utilities for the EQ-5D-5L, PROPr, SF-6D and TTO were 0.79, 0.47, 0.76 and 0.89. In corresponding order, the ceiling was 28%, 0%, 2% and 65%. The SF-6D showed excellent agreement with the EQ-5D-5L (ICC = 0.770). PROPr demonstrated poor agreement with the EQ-5D-5L (ICC = 0.381) and fair with SF-6D utilities (ICC = 0.445). TTO utilities showed poor agreement with indirectly assessed utilities (ICC = 0.058–0.242). The EQ-5D-5L better discriminated between known groups of general and physical health, while the SF-6D and PROPr outperformed the EQ-5D-5L for mental health problems.

Conclusion
There is a great variability in utilities across the four methods in patients with chronic skin conditions. The EQ-5D-5L, despite its higher ceiling, appears to be the most efficient in discriminating between patient groups for physical health aspects. Our findings inform the choice of instrument for quality-adjusted life year calculations in cost-utility analyses.
Frölicher spectral sequence of compact complex manifolds with special Hermitian metrics
Authors: Latorre Adela , Ugarte Luis , Villacampa Raquel 
Published: October 2024

AbstractIn this paper we focus on the interplay between the behaviour of the Frölicher spectral sequence and the existence of special Hermitian metrics on the manifold, such as balanced, SKT or generalized Gauduchon. The study of balanced metrics on nilmanifolds endowed with strongly non-nilpotent complex structures allows us to provide infinite families of compact balanced manifolds with Frölicher spectral sequence not degenerating at the second page. Moreover, this result is extended to non-degeneration at any arbitrary page. Similar results are obtained for the Frölicher spectral sequence of compact generalized Gauduchon manifolds. We also find a compact SKT manifold whose Frölicher spectral sequence does not degenerate at the second page, thus providing a counterexample to a conjecture by Popovici.
Anthropogenic impacts drive habitat suitability in South Asian bats
Authors: Srinivasulu Aditya , Senapathi Deepa , González-Suárez Manuela 
Published: September 2024

AbstractDespite their diversity and importance as ecological indicators and ecosystem service providers, the macroecology of bats in South Asia is poorly understood, and until recently studies on the ecological niches of these species have been rare. This study analyses the ecogeographic predictors of habitat suitability in South Asian bats by conducting ensemble ecological niche modelling using four algorithms (random forests, artificial neural networks, multivariate adaptive regression splines, and maximum entropy) to define suitability envelopes for 48 selected bat species, based on topographic, hydrographic, land-use, land-cover, and other anthropogenic impact factors. Anthropogenic impact variables showed high importance with Median Night-time Light being the biggest driver of habitat suitability for most of the study species with generally lower suitability of brighter areas. Projected suitable areas for individual species covered between 6.28% and 22.98% of the study area. Regions such as the Thar desert of northwestern India were consistently identified to have low suitability. The Western Ghats in India, the Himalayas in Bhutan, northern India, and Nepal, and Sri Lanka were identified as suitability hotspots for more than half the studied species overlapping with human-impacted habitats. This study offers insight into the impacts of anthropogenic pressure on the macroecology of bats in a megadiverse region and stresses the importance of analysing ecogeographic effects on ecological niches and habitat suitability, which can be vital to inform conservation planning and policymaking in the future.
Evaluating Negotiators Who Deceptively Communicate Anger or Happiness: On the Importance of Morality, Sociability, and Competence
Authors: Ye Zi , Lelieveld Gert-Jan , van Dijk Eric 
Published: October 2024

AbstractResearch has shown that negotiators sometimes misrepresent their emotions, and communicate a different emotion to opponents than they actually experience. Less is known about how people evaluate such negotiation tactics. Building on person perception literature, we investigated in three preregistered studies (N = 853) how participants evaluate negotiators who deceptively (vs. genuinely) communicate anger or happiness, on the dimensions of morality, sociability, and competence. Study 1 employed a buyer/seller setting, Studies 2 and 3 employed an Ultimatum Bargaining Game (UBG). In all studies, participants learned a negotiator’s (the target’s) experienced and communicated emotions (anger or happiness), before evaluating the target. Across studies, targets were evaluated lower on morality if they deceptively (vs. genuinely) communicated anger or happiness. Notably, negotiators deceptively communicating anger were evaluated lower on morality and sociability but higher on competence than those deceptively communicating happiness. Studies 2 and 3 investigated behavioral consequences by examining whether in a future negotiation participants chose the target to be their opponent or representative. Results showed that for opponents, participants preferred targets who genuinely communicated happiness (vs. anger), which was associated with their perceived morality or sociability. For representatives, participants not only preferred targets who had genuinely communicated happiness (vs. anger), but also targets who had deceptively communicated anger (vs. happiness), which was associated with their perceived competence. These findings show that when evaluating deceptive (vs. genuine) communication strategies, people distinguish between morality, sociability, and competence. The importance they attach to these dimensions is also contingent on the behavioral decisions they face.
Functional links between the microbiome and the molecular pathways of colorectal carcinogenesis
Authors: Permain Jessica , Hock Barry , Eglinton Timothy , Purcell Rachel 
Published: September 2024

AbstractColorectal cancer (CRC) is a common cancer, with a concerning rise in early-onset CRC cases, signalling a shift in disease epidemiology. Whilst our understanding of the molecular underpinnings of CRC has expanded, the complexities underlying its initiation remain elusive, with emerging evidence implicating the microbiome in CRC pathogenesis. This review synthesizes current knowledge on the intricate interplay between the microbiome, tumour microenvironment (TME), and molecular pathways driving CRC carcinogenesis. Recent studies have reported how the microbiome may modulate the TME and tumour immune responses, consequently influencing cancer progression, and whilst specific bacteria have been linked with CRC, the underlying mechanisms remains poorly understood. By elucidating the functional links between microbial landscapes and carcinogenesis pathways, this review offers insights into how bacteria orchestrate diverse pathways of CRC development, shedding light on potential therapeutic targets and personalized intervention strategies.
Socially Disruptive Technologies and Conceptual Engineering
Authors: Veluwenkamp Herman , Hopster Jeroen , Köhler Sebastian , Löhr Guido 
Published: September 2024

AbstractIn this special issue, we focus on the connection between conceptual engineering and the philosophy of technology. Conceptual engineering is the enterprise of introducing, eliminating, or revising words and concepts. The philosophy of technology examines the nature and significance of technology. We investigate how technologies such as AI and genetic engineering (so-called “socially disruptive technologies”) disrupt our practices and concepts, and how conceptual engineering can address these disruptions. We also consider how conceptual engineering can enhance the practice of ethical design. The issue features seven articles that discuss a range of topics, including trust in blockchain applications and the evolving concept of nature. These articles highlight that as technology changes the world and our concepts, conceptual engineering provides invaluable tools and frameworks to reflect on these changes and adapt accordingly.
Environmental shifts and their impact on sponge-associated macroinvertebrate communities in seagrass ecosystems
Authors: Briceño-Vera Antony Enrique , Ávila Enrique , Rodríguez-Santiago María Amparo , Nava Héctor 
Published: September 2024

AbstractThis study aimed to assess the alterations in the community structure of macroinvertebrates associated with two seagrass-dwelling sponge species following a shift in the environmental conditions. Individuals of the sponge Amorphinopsis atlantica, whose optimal distribution is in areas exposed to wind-driven waves, were transplanted to a less exposed area and, contrarily, individuals of Haliclona implexiformis, whose optimal distribution is in less exposed areas, were transplanted to an exposed area. After 71 days, individuals of A. atlantica showed a decrease in the density (75.5%), family richness (29.8%), and diversity (22.2%) of associated macroinvertebrates regarding controls, whereas those of H. implexiformis showed an increase in the density (85.9%), family richness (57.7%), and diversity (20.8%). These changes were attributed to species turnover, recruitment of some associated taxa, and morphological changes in one of the host sponge species. In the exposed site, the associated communities were more influenced by the hydrodynamism and sedimentation rate, and in the protected site, by salinity and the concentrations of organic matter in surface sediments and the water column. Overall, this study highlights the complex interactions between environmental conditions and marine biodiversity, providing valuable data for the conservation and management of seagrass meadow ecosystems and their associated sponge communities.
A self-supervised seed-driven approach to topic modelling and clustering
Authors: Ravenda Federico , Bahrainian Seyed Ali , Raballo Andrea , Mira Antonietta , Crestani Fabio 
Published: September 2024

AbstractTopic models are useful tools for extracting the most salient themes within a collection of documents, grouping them to construct clusters representative of each specific topic. These clusters summarize and represent the semantic contents of the documents for better document interpretation. In this work, we present a light approach able to learn topic representations in a Self-Supervised fashion. More specifically, we propose a lightweight and scalable architecture using a seed-word driven approach to simultaneously co-learn a representation from a document and its corresponding word embeddings. The results obtained on a variety of datasets of different sizes and natures show that our model is capable of extracting meaningful topics. Furthermore, our experiments on five benchmark datasets illustrate that our model outperforms both traditional and neural topic modelling baseline models in terms of different coherence and clustering accuracy measures.
Best practices for machine learning strategies aimed at process parameter development in powder bed fusion additive manufacturing
Authors: Samadiani Najmeh , Barnard Amanda S. , Gunasegaram Dayalan , Fayyazifar Najmeh 
Published: October 2024

AbstractThe process parameters used for building a part utilizing the powder-bed fusion (PBF) additive manufacturing (AM) system have a direct influence on the quality—and therefore performance—of the final object. These parameters are commonly chosen based on experience or, in many cases, iteratively through experimentation. Discovering the optimal set of parameters via trial and error can be time-consuming and costly, as it often requires examining numerous permutations and combinations of parameters which commonly have complex interactions. However, machine learning (ML) methods can recommend suitable processing windows using models trained on data. They achieve this by efficiently identifying the optimal parameters through analyzing and recognizing patterns in data described by a multi-dimensional parameter space. We reviewed ML-based forward and inverse models that have been proposed to unlock the process–structure–property–performance relationships in both directions and assessed them in relation to data (quality, quantity, and diversity), ML method (mismatches and neglect of history), and model evaluation. To address the common shortcomings inherent in the published works, we propose strategies that embrace best practices. We point out the need for consistency in the reporting of details relevant to ML models and advocate for the development of relevant international standards. Significantly, our recommendations can be adopted for ML applications outside of AM where an optimum combination of process parameters (or other inputs) must be found with only a limited amount of training data.
An Optimization on 2D-SLAM Map Construction Algorithm Based on LiDAR
Authors: Li Zhuoran , Chamran Kazem , Alobaedy Mustafa Muwafak , Sheikh Muhammad Aman , Siddiqui Tahir , Ahad Abdul 
Published: September 2024

AbstractWhen a mobile robot moves in an unknown environment, the emergence of Simultaneous Localization and Mapping (SLAM) technology becomes crucial for accurately perceiving its surroundings and determining its position in the environment. SLAM technology successfully addresses the issues of low localization accuracy and inadequate real-time performance of traditional mobile robots. In this paper, the Robot Operating System (ROS) robot system is used as a research platform for the 2D laser SLAM problem based on the scan matching method. The study investigates the following aspects: enhancing the scan matching process of laser SLAM through the utilization of the Levenberg–Marquardt (LM) method; improving the optimization map by exploring the traditional Hector-SLAM algorithm and 2D-SDF-SLAM algorithm, and employing the Weighted Signed Distance Function (WSDF) map for map enhancement and optimization; proposing a method for enhanced relocation using the Cartographer algorithm; establishing the experimental environment and conducting experiments utilizing the ROS robot system. Comparing and analyzing the improved SLAM method with the traditional SLAM method, the experiment proves that the improved SLAM method outperforms in terms of localization and mapping accuracy. The research in this paper offers a robust solution to the challenge of localizing and mapping mobile robots in unfamiliar environments, making a significant contribution to the advancement of intelligent mobile robot technology.
Hazards, Risks and Selected Security Problems in Unnmaned Aircraft Vehicles Operations
Authors: Osiecki Mateusz , Cyran Klaudia , Dębowski Leon 
Published: September 2024

AbstractThis article pertains to hazards and risk as well as selected security problems in unmanned aircraft vehicles operations from legal and policy perspective. It covers regulations concerning drones, statistics, safety promotion in drone sector and key risk areas. In the current world, there is a need for new legal provisions and technical solutions that will bring stability and security to public airspace. With the rapid development of artificial intelligence, more reliable hardware, and efficient software, new threats for the public domain are emerging that we have never faced before. The usage of UAVs is limited only by human imagination. It is already used in search and rescue (SAR) missions (increasing search coverage and reducing the risk of rescuers), the professional movie industry (creating breathtaking shots), or the agricultural sector (plants optimization). Hence the need to identify key safety and security concerns that might disrupt such operations.
Pre-Service Science Teachers’ Intention to use Generative Artificial Intelligence in Inquiry-Based Teaching
Authors: Ramnarain Umesh , Ogegbo Ayodele Abosede , Penn Mafor , Ojetunde Segun , Mdlalose Noluthando 
Published: September 2024

AbstractThis research investigated pre-service science teachers’ intention to use generative artificial intelligence (AI) in inquiry-based teaching using Azjen’s Theory of Planned Behavior. Quantitative data were collected by means of a survey that was administered to pre-service teachers enrolled for an undergraduate teacher education degree at a South African public university. Thereafter, through interviews, the study investigated how the pre-service teachers explained their intentions to use AI in inquiry-based teaching. The survey results showed that pre-service teachers’ AI literacy, subjective norm, attitude to the use of AI, perceived behavioral control, and perceived usefulness have significant effects on their intention to use AI for inquiry-based teaching. However, pre-service teachers’ concern about generative AI and their perceived skill readiness had no significant effect on their intention to use AI. The findings of the interviews that were presented as themes provided some corroboration of the results of the survey. In exploiting the use of AI to drive inquiry-based teaching, the findings of this study provide some insight into possible enablers and inhibitors in the use of AI for inquiry in the classroom. From a practical perspective, these findings could inform teacher educators on issues they may engage pre-service science teachers when discussing the uses of AI.
CRITERION OF THE GLOBAL SOLVABILITY OF REGULAR AND SINGULAR DIFFERENTIAL-ALGEBRAIC EQUATIONS
Authors: Filipkovska Maria 
Published: September 2024

AbstractFor regular and nonregular (singular) semilinear differential-algebraic equations (DAEs), we prove theorems on the existence and uniqueness of global solutions and on the blow-up of solutions, which allow one to identify the sets of initial values for which the initial value problem has global solutions and/or for which solutions are blow-up in finite time, as well as the regions that the solutions cannot leave. Together these theorems provide a criterion of the global solvability of semilinear DAEs. As a consequence, we obtain conditions for the global boundedness of solutions.