bluuebunny/crossref_metadata_2025_split huggingface dataset:
Signaling without Saying
Authors: Henderson Robert , McCready Elin 
Published: June 2024

Abstract
Signaling without Saying develops game-theoretic approaches to social meaning to model the phenomenon of dogwhistles. Dogwhistles, known primarily from political speech, involve language that sends one message to an out-group while at the same time sending a second (often taboo, controversial, or inflammatory) message to an in-group. We argue that dogwhistles should be treated as primarily bearing social meaning, as understood by modern variationist sociolinguistic theories. We show that dogwhistle communication can be modeled in Bayesian signaling games where speakers are attempting to signal their sociolinguistic persona to listeners who are attempting to detect the persona of their interlocuter. Dogwhistles are useful precisely when optimal play for a speaker involves hiding the sociolinguistic persona being sent to one subaudience from another subaudience. With this basic formal account in hand, this work explores dogwhistles in depth, but also a variety of related phenomena. We identify for the first time two different kinds of dogwhistle meaning, and model them. We show how novel implicatures in the social meaning domain can arise when a listener detects a dogwhistle, and connect them to implicatures familiar in the truth-conditional domain. We show how social meaning can be added to theories of trust in testimonial evidence, and explain why dogwhistles can help establish trust with an audience, even when expressing false propositions. Finally, we look at connections between dogwhistles, as we model them, and other issues important in epistemology and philosophy of language which might involve social meaning, like standpoint theory.
Stoic Tolerance?
Authors: Atkins Jed W 
Published: June 2024

Abstract
Chapter 2 examines Stoic treatments of endurance, focusing on the writings of Seneca and Marcus Aurelius. Stoicism provides an alternate ancient tradition against which to assess the contours and distinctiveness of the North African Christian tradition. The Stoic concept of endurance reveals different theological, cosmological, political, and psychological commitments than those within the North African Christian tradition. For the Stoics judgment involves recognizing that the only actions that are truly good or evil are those within one’s own power. This conception of judgment dissociates endurance from political judgment in the sense of a judgment about the common good. Stoic endurance becomes strangely apolitical and unstable: if there are no external evils to forbear, tolerance, which requires objection, disappears. Stoicism becomes simultaneously too politically quietist and too personally rigorous—a morally demanding philosophy that nevertheless leaves society largely unchanged.
Augustine on Political Judgment and Tolerance
Authors: Atkins Jed W 
Published: June 2024

Abstract
Chapter 8 examines how Augustine applies his account of judgment and patience to the controversy with the Donatists. I argue that Augustine’s so-called anti-Donatist writings deepen and extend, rather than undermine, the tradition of thinking about tolerance he inherited from Tertullian, Cyprian, and Lactantius. Augustine’s account confronts a common objection to the notion of tolerance as forbearing what one finds objectionable: doesn’t such forbearance in the face of injustice make one complicit in the resulting wrong? Augustine’s theory answers this objection by linking judgment and tolerance. One must consider one’s obligation to judge before one can tolerate. Augustine’s particular account of judgment and tolerance presupposes that human beings are social and temporal creatures. Tolerance depends on a judgment that acknowledges the realities of space and time. Conversely, to judge without properly acknowledging space and time distorts judgment and underwrites a simple dualism in the present that makes tolerance impossible.
Issues of science, history, and language
Authors: Kragh Helge 
Published: June 2024

Abstract
The language of science differs in a number of ways from ordinary language, and the relation between the two has been discussed for centuries. Eponyms and metaphors are common to the two versions, and yet they function differently. Words constantly change in meaning, such as illustrated by the words ‘atom’, ‘molecule’, and ‘scientist’, the latter a neologism coined in 1834. As discussed in one of the sections, what counts as a science has also changed over time. There are several ‘lost sciences’ no longer recognized as proper sciences. The last section deals in some detail with the history of words entering geology, a science which was only named so in the mid-seventeenth century.
Heavenly sciences
Authors: Kragh Helge 
Published: June 2024

Abstract
Surprisingly many of our common words are derived from the astronomical sciences. The planets and other celestial bodies have particular names that reflect their histories and attempts to categorize them. For example, the term ‘asteroid’ was proposed by William Herschel because he thought they looked somewhat like stars. One of the sections deals with the vocabulary associated with the belief in extraterrestrial life, including a ‘cosmic language’ with which all advanced beings in the universe can communicate. The chapter also looks at words such as nebula, galaxy, and Milky Way, and how these have been conceived in the past. The final section is devoted to names of twentieth-century cosmology of which ‘Big Bang’ coined in 1949 is probably the most successful and best known.
Development of pENTR-NeCo-lacZα vectors for the preparation of negative control constructs in Gateway cloning
Authors: Kuzuhara Taiki , Monden Kota , Hachiya Takushi , Nakagawa Tsuyoshi 
Published: June 2024

ABSTRACT
Gateway cloning is a useful technology for the simple and reliable preparation of various construct in many organisms. However, there is a problem regarding the negative control construct in the Gateway cloning system. In this study, we developed the pENTR-NeCo-lacZα vector system to create an empty vector that can be used as a negative control construct in Gateway cloning.
Effects of inbreeding and elevated rearing temperatures on strategic sperm investment
Authors: Chung Meng-Han Joseph , Mahmud-Al-Hasan Md , Jennions Michael D , Head Megan L 
Published: June 2024

Abstract
Males often strategically adjust the number of available sperm based on the social context (i.e. sperm priming response), but it remains unclear how environmental and genetic factors shape this adjustment. In freshwater ecosystems, high ambient temperatures often lead to isolated pools of hotter water in which inbreeding occurs. Higher water temperatures and inbreeding can impair fish development, potentially disrupting sperm production. We used guppies (Poecilia reticulata) to investigate how developmental temperature (26 °C, 30 °C) and male inbreeding status (inbred, outbred) influence their sperm priming response. We also tested if sperm priming was affected by whether the female was a relative (sister) and whether she was inbred or outbred. There was no effect of rearing temperature; male inbreeding status alone determined the number of available sperm in response to female presence, her inbreeding status, and her relatedness. Inbred males produced significantly more sperm in the presence of an unrelated, outbred female than when no female was present. Conversely, outbred males did not alter the number of sperm available in response to female presence or relatedness. Moreover, inbred males produced marginally more sperm when exposed to an unrelated female that was outbred rather than inbred, but there was no difference when exposed to an inbred female that was unrelated versus related. Together, a sperm priming response was only observed in inbred males when exposed to an outbred female. Outbred females in our study were larger than inbred females, suggesting that inbred males strategically allocated ejaculate resources toward females in better condition.
Hapsolutely: a user-friendly tool integrating haplotype phasing, network construction, and haploweb calculation
Authors: Vences Miguel , Patmanidis Stefanos , Schmidt Jan-Christopher , Matschiner Michael , Miralles Aurélien , Renner Susanne S 
Published: June 2024

AbstractMotivationHaplotype networks are a routine approach to visualize relationships among alleles. Such visual analysis of single-locus data is still of importance, especially in species diagnosis and delimitation, where a limited amount of sequence data usually are available and sufficient, along with other datasets in the framework of integrative taxonomy. In diploid organisms, this often requires separating (phasing) sequences with heterozygotic positions, and typically separate programs are required for phasing, reformatting of input files, and haplotype network construction. We therefore developed Hapsolutely, a user-friendly program with an ergonomic graphical user interface that integrates haplotype phasing from single-locus sequences with five approaches for network/genealogy reconstruction.ResultsAmong the novel options implemented, Hapsolutely integrates phasing and graphical reconstruction steps of haplotype networks, supports input of species partition data in the common SPART and SPART-XML formats, and calculates and visualizes haplowebs and fields for recombination, thus allowing graphical comparison of allele distribution and allele sharing among subsets for the purpose of species delimitation. The new tool has been specifically developed with a focus on the workflow in alpha-taxonomy, where exploring fields for recombination across alternative species partitions may help species delimitation.Availability and implementationHapsolutely is written in Python, and integrates code from Phase, SeqPHASE, and PopART in C++ and Haxe. Compiled stand-alone executables for MS Windows and Mac OS along with a detailed manual can be downloaded from https://www.itaxotools.org; the source code is openly available on GitHub (https://github.com/iTaxoTools/Hapsolutely).
Combined with the semantic features of CT and selected clinical variables, a machine learning model for accurately predicting the prognosis of Omicron was established
Authors: Jin Di , Li Zicong , Deng Zhikang , Nan Jiayu , Huang Pei , Zeng Bingliang , Fan Bing 
Published: June 2024

Abstract

Objectives
To efficiently use medical resources and offer optimal personalized treatment for individuals with Omicron infection, it is vital to predict the disease’s outcome early on. This research developed three machine learning models to foresee the results for Omicron-infected patients.

Methods
Data from 253 Omicron-infected patients, including their CT scans, clinical details, and relevant laboratory values, were studied. The patients were categorized into two groups based on their disease progression: favourable prognosis and unfavourable prognosis. Patients manifesting respiratory failure, acute liver or kidney impairment, or fatalities were placed in the “poor” group. Those lacking such symptoms were allocated to the “good” group. The participants were randomly split into training set (202) and validation set (51) with an 8:2 ratio. Radiomics features were produced using image processing, focused segmentation, feature extraction, and selection, leading to the establishment of a radiomics model. A univariate logistic regression method identified potential clinical factors contributing to a clinical model’s development. Eventually, the fused feature set, integrating radiomics features and clinical indicators, was used for the combined model. The model’s prediction performance was assessed using the area under the receiver operating characteristic curve (AUC). The model’s clinical usefulness was evaluated by generating calibration and decision curves.

Results
Compared to other classification models, the combined model showcased the best classification performance. It achieved an AUC of 0.848 and accuracy of 0.763 in the training set, and 0.797 and 0.750 in the validation set, respectively.

Conclusions
This study employed machine learning model to accurately predict the prognosis of Omicron-infected patients.

Advances in knowledge
(1) Topic innovation: At present, there is a lack of research on the use of CT images to construct machine learning models to predict the prognosis of patients with Omicron infection. This study intends to establish clinical, radiomics, and combined models to provide more possibilities for the identification of the two. (2) Platform innovation: The feature extraction and screening and the establishment of omics model in this study will be completed in the intelligent scientific research platform, which can reduce the error caused by human error, simplify the operation steps, and save the time of data processing time.
Immunomodulatory poly(L-lactic acid) nanofibrous membranes promote diabetic wound healing by inhibiting inflammation, oxidation and bacterial infection
Authors: Wu Yan , Zhang Jin , Lin Anqi , Zhang Tinglin , Liu Yong , Zhang Chunlei , Yin Yongkui , Guo Ran , Gao Jie , Li Yulin , Chu Yanhui 
Published: June 2024

AbstractBackgroundGiven the significant impact on human health, it is imperative to develop novel treatment approaches for diabetic wounds, which are prevalent and serious complications of diabetes. The diabetic wound microenvironment has a high level of reactive oxygen species (ROS) and an imbalance between proinflammatory and anti-inflammatory cells/factors, which hamper the healing of chronic wounds. This study aimed to develop poly(L-lactic acid) (PLLA) nanofibrous membranes incorporating curcumin and silver nanoparticles (AgNPs), defined as PLLA/C/Ag, for diabetic wound healing.MethodsPLLA/C/Ag were fabricated via an air-jet spinning approach. The membranes underwent preparation and characterization through various techniques including Fourier-transform infrared spectroscopy, measurement of water contact angle, X-ray photoelectron spectroscopy, X-ray diffraction, scanning electron microscopy, assessment of in vitro release of curcumin and Ag+, testing of mechanical strength, flexibility, water absorption and biodegradability. In addition, the antioxidant, antibacterial and anti-inflammatory properties of the membranes were evaluated in vitro, and the ability of the membranes to heal wounds was tested in vivo using diabetic mice.ResultsLoose hydrophilic nanofibrous membranes with uniform fibre sizes were prepared through air-jet spinning. The membranes enabled the efficient and sustained release of curcumin. More importantly, antibacterial AgNPs were successfully reduced in situ from AgNO3. The incorporation of AgNPs endowed the membrane with superior antibacterial activity, and the bioactivities of curcumin and the AgNPs gave the membrane efficient ROS scavenging and immunomodulatory effects, which protected cells from oxidative damage and reduced inflammation. Further results from animal studies indicated that the PLLA/C/Ag membranes had the most efficient wound healing properties, which were achieved by stimulating angiogenesis and collagen deposition and inhibiting inflammation.ConclusionsIn this research, we successfully fabricated PLLA/C/Ag membranes that possess properties of antioxidants, antibacterial agents and anti-inflammatory agents, which can aid in the process of wound healing. Modulating wound inflammation, these new PLLA/C/Ag membranes serve as a novel dressing to enhance the healing of diabetic wounds.
Spatiotemporal dynamics of cortical somatosensory network in typically developing children
Authors: Song Yanlong , Shahdadian Sadra , Armstrong Eryn , Brock Emily , Conrad Shannon E , Acord Stephanie , Johnson Yvette R , Marks Warren , Papadelis Christos 
Published: June 2024

Abstract
Sense of touch is essential for our interactions with external objects and fine control of hand actions. Despite extensive research on human somatosensory processing, it is still elusive how involved brain regions interact as a dynamic network in processing tactile information. Few studies probed temporal dynamics of somatosensory information flow and reported inconsistent results. Here, we examined cortical somatosensory processing through magnetic source imaging and cortico–cortical coupling dynamics. We recorded magnetoencephalography signals from typically developing children during unilateral pneumatic stimulation. Neural activities underlying somatosensory evoked fields were mapped with dynamic statistical parametric mapping, assessed with spatiotemporal activation analysis, and modeled by Granger causality. Unilateral pneumatic stimulation evoked prominent and consistent activations in the contralateral primary and secondary somatosensory areas but weaker and less consistent activations in the ipsilateral primary and secondary somatosensory areas. Activations in the contralateral primary motor cortex and supramarginal gyrus were also consistently observed. Spatiotemporal activation and Granger causality analysis revealed initial serial information flow from contralateral primary to supramarginal gyrus, contralateral primary motor cortex, and contralateral secondary and later dynamic and parallel information flows between the consistently activated contralateral cortical areas. Our study reveals the spatiotemporal dynamics of cortical somatosensory processing in the normal developing brain.
The effects of electrical stimulation of ventromedial prefrontal cortex on skin sympathetic nerve activity
Authors: Patel Mariya , Braun Joe A , Henderson Luke A , Dawood Tye , Macefield Vaughan G 
Published: June 2024

Abstract
Skin sympathetic nerve activity (SSNA) is primarily involved in thermoregulation and emotional expression; however, the brain regions involved in the generation of SSNA are not completely understood. In recent years, our laboratory has shown that blood-oxygen-level-dependent signal intensity in the ventromedial prefrontal cortex (vmPFC) and dorsolateral prefrontal cortex (dlPFC) are positively correlated with bursts of SSNA during emotional arousal and increases in signal intensity in the vmPFC occurring with increases in spontaneous bursts of SSNA even in the resting state. We have recently shown that unilateral transcranial alternating current stimulation (tACS) of the dlPFC causes modulation of SSNA but given that the current was delivered between electrodes over the dlPFC and the nasion, it is possible that the effects were due to current acting on the vmPFC. To test this, we delivered tACS to target the right vmPFC or dlPFC and nasion and recorded SSNA in 11 healthy participants by inserting a tungsten microelectrode into the right common peroneal nerve. The similarity in SSNA modulation between ipsilateral vmPFC and dlPFC suggests that the ipsilateral vmPFC, rather than the dlPFC, may be causing the modulation of SSNA during ipsilateral dlPFC stimulation.
MechanoProDB: a web-based database for exploring the mechanical properties of proteins
Authors: Mesbah Ismahene , Habermann Bianca , Rico Felix 
Published: June 2024

Abstract
The mechanical stability of proteins is crucial for biological processes. To understand the mechanical functions of proteins, it is important to know the protein structure and mechanical properties. Protein mechanics is usually investigated through force spectroscopy experiments and simulations that probe the forces required to unfold the protein of interest. While there is a wealth of data in the literature on force spectroscopy experiments and steered molecular dynamics simulations of forced protein unfolding, this information is spread and difficult to access by non-experts. Here, we introduce MechanoProDB, a novel web-based database resource for collecting and mining data obtained from experimental and computational works. MechanoProDB provides a curated repository for a wide range of proteins, including muscle proteins, adhesion molecules and membrane proteins. The database incorporates relevant parameters that provide insights into the mechanical stability of proteins and their conformational stability such as the unfolding forces, energy landscape parameters and contour lengths of unfolding steps. Additionally, it provides intuitive annotations of the unfolding pathways of each protein, allowing users to explore the individual steps during mechanical unfolding. The user-friendly interface of MechanoProDB allows researchers to efficiently navigate, search and download data pertaining to specific protein folds or experimental conditions. Users can visualize protein structures using interactive tools integrated within the database, such as Mol*, and plot available data through integrated plotting tools. To ensure data quality and reliability, we have carefully manually verified and curated the data currently available on MechanoProDB. Furthermore, the database also features an interface that enables users to contribute new data and annotations, promoting community-driven comprehensiveness. The freely available MechanoProDB aims to streamline and accelerate research in the field of mechanobiology and biophysics by offering a unique platform for data sharing and analysis. MechanoProDB is freely available at https://mechanoprodb.ibdm.univ-amu.fr.
Capabilities, sustainability, and innovation in mining value chains
Authors: Pietrobelli Carlo , Casaburi Gabriel , Iizuka Michiko 
Published: June 2024

Abstract
The original research presented in this Special Section analyzes different aspects of the potential offered to mining firms in developing countries by new demands for solutions to face environmental, social and technological challenges. The evidence is drawn from extensive fieldworks and comparative econometric research on Latin America, and suggests that the existing opportunities will need to be pursued with firm-level efforts and active regulatory and innovation policies.
Optimal generation expansion planning model for solar PV generation on Run of River-based hydro-based power system using binary genetic algorithm
Authors: Pathak Kaushaki , Chaudhary Sandhya , Bhandari Murahari Prasad , Sharma Pragati , Poudel Nawaraj , Neupane Deependra 
Published: June 2024

Abstract
This paper presents a binary genetic algorithm approach developed to solve the optimal generation expansion planning problem for solar photo-voltaic (PV) based Run of River (ROR) hydro generation systems. The results show that the methodology effectively solves mixed-integer, constrained nonlinear generation expansion problems. The model is then used to optimize the generation expansion problem for the electricity grid in the eastern region of Nepal, considering the under construction and planned solar PV and ROR-based hydropower plants. The optimal problem is formulated to determine the optimal number, location and type of power plant to fulfill the demand for the electricity grid of the eastern zone grid of Nepal. Results show that the total generation from the optimal sites combining hydro and solar sites is found to be about 26% of that of total energy in the Nepalese grid. However, the total demand in the system under consideration for the year is about 1352 GWh. With eliminating line losses, a surplus generation of about 1377 GWh has been found. This surplus can be used as power pooling with neighboring countries. The system has a surplus during the wet season but needs to be improved during the dry season. Hence, appropriate policies can be formulated for power banking and pooling to balance the demand–supply in the system.