bluuebunny/crossref_metadata_2025_split huggingface dataset:
Coaching Based on Signature Strengths or Lesser Strengths? The Effects of Two Strengths Spotting Interventions on Managerial Coaching Behavior
Authors: Tobias Valesca Y. , van Woerkom Marianne , Meyers Maria Christina , Bauwens Robin 
Published: May 2024

AbstractManagers are increasingly expected to coach their employees. However, managers are often ill equipped and lack the necessary support from their organization to effectively implement coaching behavior. Based on strengths theory, we propose that a strengths spotting intervention could help managers to develop their coaching behavior. In addition, based on theory on emotional contagion and the broaden and build theory, we argue that spotting employees’ signature strengths leads to a stronger increase in managerial coaching behavior over time than an intervention that focuses on spotting lesser strengths. We conducted a field experiment, in which 255 managers (providing 414 data points) were randomly assigned to either a signature strengths or a lesser strengths spotting intervention. In a 1-month follow-up study we found that both interventions contributed equally to managerial coaching behavior. We conclude that online training in strengths spotting is a useful tool that helps managers to develop their coaching behavior.
Nanofluidic Platform for Studying the First-Order Phase Transitions in Superfluid Helium-3
Authors: Heikkinen Petri J. , Eng Nathan , Levitin Lev V. , Rojas Xavier , Singh Angadjit , Autti Samuli , Haley Richard P. , Hindmarsh Mark , Zmeev Dmitry E. , Parpia Jeevak M. , Casey Andrew , Saunders John 
Published: May 2024

AbstractThe symmetry-breaking first-order phase transition between superfluid phases $$^3$$

3

He-A and $$^3$$

3

He-B can be triggered extrinsically by ionising radiation or heterogeneous nucleation arising from the details of the sample cell construction. However, the role of potential homogeneous intrinsic nucleation mechanisms remains elusive. Discovering and resolving the intrinsic processes may have cosmological consequences, since an analogous first-order phase transition, and the production of gravitational waves, has been predicted for the very early stages of the expanding Universe in many extensions of the Standard Model of particle physics. Here we introduce a new approach for probing the phase transition in superfluid $$^3$$

3

He. The setup consists of a novel stepped-height nanofluidic sample container with close to atomically smooth walls. The $$^3$$

3

He is confined in five tiny nanofabricated volumes and assayed non-invasively by NMR. Tuning of the state of $$^3$$

3

He by confinement is used to isolate each of these five volumes so that the phase transitions in them can occur independently and free from any obvious sources of heterogeneous nucleation. The small volumes also ensure that the transitions triggered by ionising radiation are strongly suppressed. Here we present the preliminary measurements using this setup, showing both strong supercooling of $$^3$$

3

He-A and superheating of $$^3$$

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He-B, with stochastic processes dominating the phase transitions between the two. The objective is to study the nucleation as a function of temperature and pressure over the full phase diagram, to both better test the proposed extrinsic mechanisms and seek potential parallel intrinsic mechanisms.
Modal tense: if and wish
Authors: Crowley Paul 
Published: May 2024

AbstractThis paper is concerned with uses of certain morphemes, most notably the past, to represent meanings of distance from reality in modal expressions. This class of morphology has been identified with the names subjunctive, fake tense, fake past, modal past and is referred to here as X-marking, after von Fintel and Iatridou (Linguist Philos, 2020). X-marking has been most studied in the context of English conditionals however, it is well-known that the morphology is observed in many non-English languages and can appear in various other types of constructions, including counterfactual desire expressions. I motivate two desiderata for theories of X-marking in pursuit of an analysis that unifies the phenomenon across expression types and languages. I then develop a novel, formally explicit analysis of X-marking which I show to satisfy these desiderata while providing greater empirical coverage of well-known cases compared to existing accounts. The proposed analysis makes use of modal presupposition projection together with pragmatic inference via Maximize Presupposition to provide a unified treatment of X-marking in English conditionals and counterfactual desires expressions of English featuring wish. I show how previous proposals for X-marking cannot satisfy these desiderata, making them insufficient for a unified account. Lastly, I introduce a hypothesis that all varieties of morphology that can be used as X-marking cross-linguistically-including past, imperfective, plural and habitual-are vacuous in both their X-marked and ordinary uses.
Multi-step Transfer Learning in Natural Language Processing for the Health Domain
Authors: Manaka Thokozile , Zyl Terence Van , Kar Deepak , Wade Alisha 
Published: May 2024

AbstractThe restricted access to data in healthcare facilities due to patient privacy and confidentiality policies has led to the application of general natural language processing (NLP) techniques advancing relatively slowly in the health domain. Additionally, because clinical data is unique to various institutions and laboratories, there are not enough standards and conventions for data annotation. In places without robust death registration systems, the cause of death (COD) is determined through a verbal autopsy (VA) report. A non-clinician field agent completes a VA report using a set of standardized questions as guide to identify the symptoms of a COD. The narrative text of the VA report is used as a case study to examine the difficulties of applying NLP techniques to the healthcare domain. This paper presents a framework that leverages knowledge across multiple domains via two domain adaptation techniques: feature extraction and fine-tuning. These techniques aim to improve VA text representations for COD classification tasks in the health domain. The framework is motivated by multi-step learning, where a final learning task is realized via a sequence of intermediate learning tasks. The framework builds upon the strengths of the Bidirectional Encoder Representations from Transformers (BERT) and Embeddings from Language Models (ELMo) models pretrained on the general English and biomedical domains. These models are employed to extract features from the VA narratives. Our results demonstrate improved performance when initializing the learning of BERT embeddings with ELMo embeddings. The benefit of incorporating character-level information for learning word embeddings in the English domain, coupled with word-level information for learning word embeddings in the biomedical domain, is also evident.
Scalable approach to create annotated disaster image database supporting AI-driven damage assessment
Authors: Ro Sun Ho , Gong Jie 
Published: May 2024

AbstractAs coastal populations surge, the devastation caused by hurricanes becomes more catastrophic. Understanding the extent of the damage is essential as this knowledge helps shape our plans and decisions to reduce the effects of hurricanes. While community and property-level damage post-hurricane damage assessments are common, evaluations at the building component level, such as roofs, windows, and walls, are rarely conducted. This scarcity is attributed to the challenges inherent in automating precise object detections. Moreover, a significant disconnection exists between manual damage assessments, typically logged-in spreadsheets, and images of the damaged buildings. Extracting historical damage insights from these datasets becomes arduous without a digital linkage. This study introduces an innovative workflow anchored in state-of-the-art deep learning models to address these gaps. The methodology offers enhanced image annotation capabilities by leveraging large-scale pre-trained instance segmentation models and accurate damaged building component segmentation from transformer-based fine-tuning detection models. Coupled with a novel data repository structure, this study merges the segmentation mask of hurricane-affected components with manual damage assessment data, heralding a transformative approach to hurricane-induced building damage assessments and visualization.
Experimental investigation of a sun tracking concentrated solar still with economic analysis
Authors: Daif Mohammad M. , Emam Mohamed , Abdelrahman M. A. , Attia Ahmed A. A. , Soliman Aly M. A. 
Published: May 2024

AbstractThe current paper evaluated experimentally an innovative sun tracking concentrated solar still under Egyptian climatic conditions during the summer of 2022. The proposed system consists of a 120-cm-diameter parabolic reflector mirror that tracks the sun using a dual axis tracking system, a cylindrical solar still with a volume of 3.7 L positioned in its focal point, and a concentration ratio of 12.5. The performance of the concentrated solar still was investigated in the context of two critical parameters. First, three feed water salinity (17, 27, 37) ppt samples were evaluated, followed by four percentages of saline water filling ratio (26.5, 39.8, 53.1, 66.3)%. Increasing the salinity of the feed water had no effect on solar still productivity, but increasing the saline water filling ratio did. The daily cumulative productivity of the system was 6 kg/m2 with an optimal filling ratio of 53.1%, a daily efficiency of 42.88%, and an average cost of freshwater production of 0.0489 $/L. The proposed system also had the highest instantaneous efficiency of 61.77% and the highest distilled water productivity rate of 0.941 kg/h m2.
Management of caffeine in wastewater using MOF and perovskite materials: optimization, kinetics, and adsorption isotherm modelling
Authors: Essam Amira , Eldek Samaa Imam , Shehata Nabila 
Published: May 2024

AbstractPharmaceuticals and personal care products (PPCPs) have been increasingly used all over the world and they have been reported on water cycle and cause contamination. Among these pharmaceuticals is caffeine (CAF). In this work, CAF removal from aqueous samples by metal–organic framework (UIO-66) and perovskite (La0.7Sr0.3FeO3) was achieved. Detailed studies on the preparation of MOFs and perovskite oxides compounds have been presented. Extensive characterizations such as X-Ray diffraction (XRD), field emission scanning electron microscope (FESEM), Fourier transform infrared spectra (FT-IR), N2 adsorption–desorption isotherms were also carried out to assure proper formation and to better understand the physico-chemical behavior of the synthesized samples before and after adsorption. Batch experiments of CAF adsorption onto both MOFs and perovskite were performed to compare the effectiveness of both materials on the removal competence of the CAF residue at different conditions including the effect of pH, initial concentration, and contact time. It was observed that the adsorption capacity of CAF by MOF increased with increasing acidity. On the other hand, the adsorption capacity of perovskite is stable in pH 4–10. The maximum adsorption capacities of UiO-66 and perovskite toward CAF are high as 62.5 mg g−1 and 35.25 mg g−1, respectively. Equilibrium isotherms were investigated by numerous models: Langmuir, Freundlich, Temkin, Redlich-Peterson, Sips, Langmuir-Freundlich, Toth, Kahn, Baudu, and Fritz Schlunder. Moreover, the kinetics of the CAF@MOF and CAF@Perovskite systems have been studied by five kinetic models (Pseudo-1st -order (PFO), Pseudo-2nd -order (PSO), Mixed 1st, 2nd-order, Intraparticle diffusion and Avrami). The best model described the adsorption of CAF onto both of MOF and perovskite was the mixed 1st, 2nd-order model. The metal–organic framework and perovskite were applied to quickly extract CAF from water samples successfully. The maximum removal percentage obtained for MOF and perovskite was 0.89% and 0.94% respectively within 30 min contact time which suggests that these materials are considered as promising adsorbents for CAF.
A big data analysis of the adoption of quoting encouragement policy on Twitter during the 2020 U.S. presidential election
Authors: Bodaghi Amirhosein , Zhu Jonathan J. H. 
Published: May 2024

AbstractThis research holds significance for the fields of social media and communication studies through its comprehensive evaluation of Twitter’s quoting encouragement policy enacted during the 2020 U.S. presidential election. In addressing a notable gap in the literature, this study introduces a framework that assesses both the quantitative and qualitative effects of specific platform-wide policy interventions, an aspect lacking in existing research. Employing a big data approach, the analysis includes 304 million tweets from a randomly sampled cohort of 86,334 users, using a systematic framework to examine pre-, within-, and post-intervals aligned with the policy timeline. Methodologically, SARIMAX models and linear regression are applied to the time series data on tweet types within each interval, offering an examination of temporal trends. Additionally, the study characterizes short-term and long-term adopters of the policy using text and sentiment analyses on quote tweets. Results show a significant retweeting decrease and modest quoting increase during the policy, followed by a swift retweeting resurgence and quoting decline post-policy. Users with fewer connections or higher activity levels adopt quoting more. Emerging quoters prefer shorter, positive quote texts. These findings hold implications for social media policymaking, providing evidence for refining existing policies and shaping effective interventions.
Irradiation-assisted synthesis of smart hydrogels based on nanomagnetic semi-interpenetrating p(HEMA)/PVP networks for the cleaning of cultural heritage artifacts
Authors: Rafiei-Sarmazdeh Zahra , Sheikh Nasrin 
Published: May 2024

AbstractPreservation of our cultural and historical heritage as a testimony to our shared past is a responsibility that demands significant attention. One of the most critical and delicate aspects of conserving such treasures is cleaning them safely and effectively. Chemical hydrogels specifically designed for cleaning cultural heritage artifacts allow for the containment and controlled release of water. Based on a generic approach, a smart nanomagnetic hydrogel was developed using a semi-interpenetrating polymer network (semi-IPN) of polyhydroxyethyl methacrylate (p(HEMA)) and polyvinyl pyrrolidone (PVP). Gamma irradiation was employed to perform simultaneous in-situ polymerization, crosslinking, and also immobilization of iron oxide magnetic nanoparticles (MNPs). The chemical and structural characteristics of the nanomagnetic hydrogel were investigated using gel content, equilibrium water content, field-emission scanning electron microscopy, magnetic properties, compressive strength, dehydration kinetics, and adhesion tests. The optimal formula for smart hydrogel was a ratio of monomer to polymer 50:50, a water content of 60 wt.%, a gamma radiation dose of 20 kGy, and 3 wt.% of MNP. Two cotton canvas case studies demonstrate the versatility and effectiveness of the selected hydrogel in removing dirt and confining the water-based cleaning system. It was found that no color leaching occurred during the cleaning process.
Conversion of infected pine wood into energy charcoal material based on a transportable carbonization system
Authors: Ni Liangmeng , Gao Qi , Ren Hao , Su Mengfu , Rong Shaowen , Liu Zhijia 
Published: May 2024

AbstractTo prevent the spread of pine wilt disease (PWD), a transportable carbonization equipment was designed for in-situ treatment of infected pine wood (IPW). The equipment killed all pine wood nematodes (PWNs) in IPW when carbonization temperature was up to 200 °C. The optimal laboratory process of infected pine wood charcoal (IPWC) was carbonization temperature of 500 °C, heating rate of 3 °C min−1 and holding time of 0 min. Based on the optimal laboratory process, the transportable carbonization equipment produced IPWC with a fixed carbon content of 79.82%, and ash content of 1.14% and a moisture content of 7.83%, which meets the requirements of EN 1860-2:2005(E) standard. The economic efficiency of incineration (T1 mode), crushing (T2 mode), and transportable carbonization (T3 mode) was evaluated. For each ton of IPW treatment, the profit generated was −75.48 USD in T1 mode, 26.28 USD in T2 mode, and 51.91 USD in T3 mode. T3 mode had the highest economic efficiency. These findings will be helpful to provide guidance for the control of PWD and value-added utilization of IPW.
Graphical Abstract
Organ Failure: A Computational Model and Perspective
Authors: Periola Ayodele A. , Sesham S. , Suresh N. 
Published: May 2024

AbstractOrgan failure in biological systems is perceived as a physiological failure which is addressable via organ transplantation. Transplantation is challenging when donor organs are not easily available. Therefore, the development of a perspective capable of yielding potential therapies is required. The presented research addresses this problem and considers the biological system’s poly-computing capability. The proposed solution considers that the organs are biological computing nodes. It considers that organ failure arises when biological computing nodes don’t perform their expected function. The proposed approaches are the micro-brain and macro-brain consciousness paradigm (MMCP) and evolutionary consciousness paradigm (ECP). MMCP and ECP describe aspects concerning the relations, synaptic evolution, communication, and adaptation to handle multi-sensory inputs. The research describes how MMCP and ECP influence technology and application development. Furthermore, performance evaluation is done to investigate the operational duration of the concerned biological entities. Analysis shows that using the proposed approach enhances the operational duration by an average of (25.2–54.1)%.
Contamination and pesticide multiresidue analysis in cotton production systems in Benin
Authors: Eclou Innocent Benjamin , Glèlè Kakaï Romain 
Published: May 2024

AbstractHigh quantity of chemical pesticides spraying in conventional cotton production systems may affect negatively natural ecosystems components. This study examined the contamination levels of soil in Benin's cotton production system in West Africa by residues of pesticides used in cotton farming. One hundred and fourteen soil samples from six conventional and organic cotton production systems were collected and analysed. Multi-class pesticide residues were extracted from the soil samples, and analysed using respectively modified QuEChERS extraction and LC–MS/MS chromatography methods. Results showed an overall soil contamination to emamectin benzoate (18.5 μg/kg), imidacloprid (116.3 μg/kg), profenofos (12.7 μg/kg), acetamiprid (10.8 μg/kg), triasophos (12.6 μg/kg), abamectin (14.3 μg/kg), and deltamethrin (10.4 μg/kg). Especially, emamectin benzoate was detected with a high contamination in Banikoara district (18.5 μg/kg). Nevertheless, these contaminations were not deemed threatening from a toxicological perspective. Soils in conventional cotton cultivation displayed lower organic matter levels but higher concentrations of pesticides, whereas soils in organic cotton cultivation were less degraded and contaminated. Consequently, it is imperative to conduct environmental risk assessments and monitor key pesticide metabolites to establish sustainable cotton production systems in Benin.
ON THE SET OF BETTI ELEMENTS OF A PUISEUX MONOID
Authors: CHAPMAN SCOTT T. , JANG JOSHUA , MAO JASON , MAO SKYLER 
Published: May 2024

AbstractLet M be a Puiseux monoid, that is, a monoid consisting of nonnegative rationals (under standard addition). In this paper, we study factorisations in atomic Puiseux monoids through the lens of their associated Betti graphs. The Betti graph of
$b \in M$
is the graph whose vertices are the factorisations of b with edges between factorisations that share at least one atom. If the Betti graph associated to b is disconnected, then we call b a Betti element of M. We explicitly compute the set of Betti elements for a large class of Puiseux monoids (the atomisations of certain infinite sequences of rationals). The process of atomisation is quite useful in studying the arithmetic of Puiseux monoids, and it has been actively considered in recent literature. This leads to an argument that for every positive integer n, there exists an atomic Puiseux monoid with exactly n Betti elements.
A methodological proposal for conlang evaluation
Authors: Peterson David , Peterson Jessie 
Published: May 2024

Abstract
Intentional language creation is a mainstay of the modern world, having gained widespread notoriety in popular television shows and films, and even finding a home in academia in the form of undergraduate courses on invented languages. In this paper, we argue that constructed languages deserve more careful consideration than they currently receive either inside or outside academia. We provide guidelines for developing evaluative criteria to be used with constructed languages of various types and ask readers, whether academics or not, to consider the role they play as audience and critics in the unfolding of a new art form: the art of language invention.