bluuebunny/crossref_metadata_2025_split huggingface dataset:
Do research universities specialize in disciplines where they hold a competitive advantage?
Authors: Abramo Giovanni , Apponi Francesca , D’Angelo Ciriaco Andrea 
Published: September 2024

AbstractEnhancing the effectiveness and efficiency of national research systems is a top priority on the policy agendas of many countries. This study focuses on one aspect of the macroeconomic efficiency of research systems: whether research institutions specialize in scientific domains where they have a competitive advantage. To evaluate this, we developed a novel methodology. This methodology measures the scientific specialization indices of each organization in various research fields and assesses their relative research productivity. It then examines the correlation between these scores and between the resulting rankings. We applied this methodology to Italian universities. We found that a significant rank correlation between universities’ field specialization and their performance appears only in a few areas, and overall, the rankings are completely unrelated. Providing such data to research managers and policymakers can help inform strategies to enhance both micro- and macro-level efficiency.
Navigating Complexity: Potentials and Paradoxes Within Governance Strategies for Public and Third Sector Collaboration
Authors: Olvik Jannita 
Published: September 2024

AbstractContemporary governance increasingly emphasizes cross-sector collaboration to address complex societal challenges. This article examines how state strategies approach cross-sector collaborations involving the third sector, and delves into the interplay of authoritative, competitive, and collaborative governance strategies within these policies. Motivated by concerns about child poverty and social exclusion, the Declaration on Leisure Activities exemplifies Norway's reliance on partnerships between government, municipalities, and third sector organizations in the leisure and culture policy field. Employing a qualitative document analysis, the study reveals both potentials and paradoxes inherent in these approaches, offering valuable insights for designing effective cross-sector policies and navigating the complexities of cross-sector collaboration.
Variation in soil water content and groundwater levels across three land cover types in a floodplain of the Kromme catchment, South Africa
Authors: Jumbi Faith , Glenday Julia , Mazvimavi Dominic 
Published: September 2024

AbstractInvasions of floodplains and riparian areas by alien woody species replacing predominantly herbaceous indigenous vegetation have altered the hydrological and ecosystem functioning in catchments. Although existing studies have examined changes in river flows following the establishment or clearing of alien woody vegetation, our understanding of impacts on soil water content and groundwater remains poor. Limited process knowledge restricts our capacity to reliably model and predict the impacts of land cover changes. As such, this work compared temporal variations in soil water content (SWC) and groundwater levels at three locations with different vegetation types: black wattle (Acacia mearnsii) trees, palmiet (Prionium serratum), and grass (dominated by Pennisetum clandestinum spp), within a floodplain site in the Kromme Catchment in the Eastern Cape Province of South Africa. Soil water content and shallow groundwater levels (< 4 m below ground) were monitored from August 2017 to December 2019 using soil moisture probes and piezometers. Rainfall, vegetation type and antecedent conditions were identified as the major factors controlling observed responses. On average, soil water content and water retention were significantly higher (p < 0.05) at the palmiet site, whilst the wattle site had the lowest SWC among the three sites. Shallow groundwater levels were also higher at the palmiet and grass sites and lowest at the wattle site. Results showed the negative impacts of black wattle trees on SWC and groundwater levels. These results are crucial for improved quantitative predictive capacity which would allow for better catchment management, for example, informing water supply planning and guiding restoration programs focusing on alien plant clearing.
Enhanced Remediation of Polycyclic Aromatic Hydrocarbons in Soil Through Fungal Delignification Strategy and Organic Waste Amendment: A Review
Authors: Omoni Victor Taghoghor , Bankole Paul Olusegun , Semple Kirk Taylor , Ojo Adesola Samson , Ibeto Cynthia , Okekporo Stephen Efe , Harrison Idorenyin Ambrose 
Published: September 2024

AbstractNutrient-limited soils from growing global contamination with polycyclic aromatic hydrocarbons (PAHs) and the massive organic waste generation from agro-based and food industries have raised more demand for exploring and recycling the latter as sustainable, cost-effective, and green nutrient-rich sources for soil amendment. To further enhanced the potentials of these substrates in soil, immobilisation or biological pre-treatment techniques using fungi are employed. The white-rot fungi- basidiomycetes, are the most widely researched and efficient organisms to perform these functions because of their high lignin-degrading ability for organic materials, such as corn cob, straws, spent brewery grains, sugarcane bagasse, etc. This review addresses the importance of organic amendment to enhance the biodegradation efficiency of PAH from contaminated soils and it also highlights various biological techniques for improving PAH biodegradation using organic waste materials and white-rot basidiomycetes. This review will also show a better understanding of the concepts of fungal immobilisation and pre-treatment for PAH degradation in soil and show their insights as feasible and optimise techniques for developing remedial strategies for contaminated soils.
Isotropic Growth on Cartesian Voxel Grids with von Neumann Neighborhoods for Rapid Generation of Synthetic Microstructures
Authors: Payton E. J. , Coutinho Y. A. , Gerlt A. R. C. , Simmons J. P. , Gonzales M. , Semiatin S. L. 
Published: September 2024

AbstractRandomized instantiations of synthetic microstructures are needed to assess the statistical significance of microstructure variability. Algorithms that use Voronoi tessellations of random points produce synthetic polycrystalline microstructures with a less realistic appearance than random packing of spheroidal particles followed by growth-until-impingement. Additionally, Voronoi tessellations offer limited control of morphological parameters and are challenging to implement when the desired volume fraction is less than unity. However, unless additional physics-based constraints are applied, growth on a Cartesian voxel grid utilizing a von Neumann neighborhood element results in anisotropic growth that is generally not observable along the primary axes. The present work describes both analytical and empirically optimized corrections for directional growth rates and a framework for their inclusion in a synthetic microstructure generation algorithm. The presented algorithm can produce synthetic microstructures similar to those produced by random seed Monte Carlo techniques in a fraction of the computational time.
Changing Medical Student Perceptions of Mental Illness Through a Psychiatry Clinical Clerkship: A Longitudinal Qualitative Study
Authors: Manley Amy E. , Biddle Lucy , Savović Jelena , Moran Paul 
Published: September 2024

Abstract
Objective
This study sought to understand whether perceptions of mental illness change during the course of students’ psychiatry clerkships, and what facilitates such change.

Methods
Using a longitudinal qualitative study design, the authors followed up 14 medical students, interviewing them before, during, and after their psychiatric clerkship.

Results
Prior to clerkships, students perceived psychiatric patients to be dangerous, fragile, hard to treat, and to exert a disproportionate emotional toll on clinicians. Stigma was reinforced by safety measures including the provision of alarms, but this improved following “real life” engagement with patients. Students experienced little emotional distress from clinical contacts, particularly those where they led the consultation. Pre-existing beliefs about mental illness being hard to “fix” showed less change over time. Although uncommon, when staff referred to patients using pejorative language, students emulated these negative attitudes.

Conclusions
Among medical students, direct patient contact plays an important role in counteracting pre-existing negative attitudes towards mental illness. This can be facilitated by supportive supervisors, clinical teams allocating students a clear practical role, involving patients in teaching, and roleplay to alleviate potential concerns about seeing patients.
Dual-Mode Colorimetric and Fluorescent Detection of Tumor Cells Based on Gold Nanoparticles-Loaded Phosphine Covalent Organic Frameworks
Authors: Li Bilian , Zhou Min , Zhao Chun , Xiao Lin , Qi Tianle , Xu Hanbin , Guo Linjiang , Ning Guobao , Lu Xiaokang , Zhu Keming , Zhao Hui , Li Can-Peng 
Published: September 2024

Abstract
Circulating tumor cells (CTCs) are important markers for cancer. The part of tumor cells that are detached from the primary tumor or metastatic tumor and enter the blood circulation is called CTCs. It is crucial to develop a rapid, accurate, and easy-to-implement diagnostic system for CTCs for early tumor diagnosis and for monitoring progression of the disease. In this work, we reported a colorimetric and fluorescent dual-mode assay for the detection of CTCs. Our assay used magnetic nanoparticles and aptamer for CTCs capture and gold nanoparticles-loaded covalent organic frameworks (Au@COFs) for signal amplification, respectively. The magnetic nanoparticles were modified with folic acid to capture CTCs by interaction between folic acid and the folate receptor overexpressed on the surface of tumor cells. The covalent organic frameworks were engineered to have both nitro-reductase-like and glucose–oxidase-like activities. The nitro-reductase-like activity converted the substrate p-nitrophenol to p-nitroaniline for colorimetric detection, and the glucose-oxidase-like activity enabled fluorescence detection. Specifically, Au@COFs catalyzed glucose oxidation and generated hydrogen peroxide to oxidize Fe2+ to Fe3+, which converted MIL(Al)-MOF to MIL(Fe)-MOF through ion exchange, resulting in the fluorescence quenching of MIL(Al)-MOF. Our assay showed high sensitivity with a detection limit of 17 cells/mL using MCF-7 cells as model cancer cells. This work provided an efficient and ultrasensitive strategy for CTCs detection and has potential applications in cancer identification and diagnosis. Dual-mode detection system, combining colorimetric and fluorescent signals, integration of magnetic nanoparticles and aptamers for CTC capture, and utilization of covalent organic frameworks loaded with gold nanoparticles for signal amplification can improve sensitivity and accuracy.
Leaders’ perceptions of digitalisation in K–12 education: influencing arrangements for leading the expansion of digital technologies
Authors: Reis-Andersson Jussara 
Published: September 2024

AbstractThis paper aims to contribute knowledge about the influences of leaders’ perceptions of digitalisation on arrangements for leading the expansion of access to and application of digital technologies in K–12 education. Supporting the digitalisation of K–12 education requires digital competence. School organisers’ and school leaders’ digital competence and perceptions of digitalisation contribute to how digital technologies are employed in schools. Survey and participant observations were used to investigate leaders’ perceptions of digitalisation in K–12 education. The data were analysed using thematic analysis and theory of practice architecture. The results show that perceptions of digitalisation in K–12 education influence arrangements by allowing opportunities for enhanced quality in teaching and equality within and among schools. Further, collaborations between leaders, sharing ideas and experiences, and enhancing leadership are elements that contribute to the shaping of leaders’ perceptions of digitalisation in schools. This paper contributes to the knowledge of leaders’ perceptions of expanding the access to and application of digital technologies in schools.
Antibiotic utilization trends in Veterans Affairs patients with Stenotrophomonas maltophilia bloodstream infections
Authors: Lee Clara H. , Patel Ursula C. , Vivo Amanda , Cao Lishan , Evans Charlesnika T. 
Published: September 2024

Abstract

Objective:
Stenotrophomonas maltophilia is a multidrug-resistant gram-negative bacillus that can cause serious infections but has limited treatment options. This study aims to establish trends in the treatment of S. maltophilia bloodstream infections (BSI) across the United States in Department of Veterans Affairs (VA) facilities.

Methods:
Data was evaluated over a 10-year timeframe (2012 to 2021) in this retrospective cohort study. Veterans with ≥ 1 blood culture with S. maltophilia within a VA medical encounter were included. Microbiology, pharmacy, and patient information were collected through national VA data sources and chart review. Descriptive statistics and Poisson regression were used to summarize patient demographics, facility characteristics, microbiologic data, and treatment trends.

Results:
A total of 374 blood cultures positive for S. maltophilia were identified across 75 VA facilities. Of 282 unique patients with BSI, the majority were male (93.6%), white (67.4%), with a mean age of 64 ± 13.1 years. Of those patients, 78% received treatment, 12.8% had a polymicrobial blood culture, and 5.3% had a documented sulfa allergy. Susceptibility results were most reported for trimethoprim-sulfamethoxazole (TMP-SMX), levofloxacin, and ceftazidime, with 4.5%, 4.3%, and 44.4% resistant isolates, respectively. Antibiotics most prescribed included TMP-SMX (41.5%) and levofloxacin (39.4%), followed by ciprofloxacin (13.8%) and ceftazidime (12.4%). Combination therapy was prescribed in 33% of patients. No significant trends were found with antibiotic utilization over time.

Conclusions:
TMP-SMX and levofloxacin were the most prescribed antibiotics for S. maltophilia BSI treatment. No significant changes were seen with antibiotic prescribing trends in Veterans from 2012 to 2021.
Procedural risk factors for deep and organ/space surgical site infection post-coronary artery bypass graft surgery
Authors: Pearl Abarna , Gordon Patrick S. , Feeser Baevin S. , Pepe Dana E. , Mehrotra Preeti , Wright Sharon B. 
Published: September 2024

Abstract
In this study, we examined the impact of the number and type of arterial grafts, and surgical dressing type, on deep and organ/space surgical site infection following coronary artery bypass graft procedures. Bilateral internal mammary artery grafts and negative pressure wound therapy were associated with higher odds of infection.
When Is it Right to Speak of Animal Rights?
Authors: McConnell Lee 
Published: September 2024

AbstractThis article examines the ways in which the language of legal rights is invoked by those seeking to improve the treatment of animals. Drawing from a range of analytical, realist, and critical legal and social theorists, it argues that certain argumentative techniques commonly employed to justify the extension of legal rights to animals may serve to strengthen and reproduce the very forms of exploitation they seek to challenge. The article begins by identifying and critiquing the binary characterisation of rights/welfare and property/personality in liberal animal law scholarship. It then employs the insights of Theodor Adorno and Walter Benjamin to expose and critique various appeals to an ‘exterior’ or ‘extra-legal’ domain which functions to stabilise the meaning of these doctrinal categories. In doing so, it explores the strategic viability of rights discourse in the animal advocacy movement with a view to highlighting the limitations of liberal constructions of animal rights.
Moral Pluralism and Constitutional Horizontality
Authors: Kohavi Tom 
Published: September 2024

AbstractDespite the growing influence of constitutional rights over the regulation of horizontal (private) relations, many aspects of this trend remain under-theorized. This article criticizes four ideal-typical constitutional horizontality models for failing to accommodate moral reasons that must shape this regulatory practice: the state action model ignores basic consequentialist aspects of political morality; the direct application model ignores basic relational aspects of interpersonal morality; the strong indirect model recognizes both but subordinates the latter to the former; and the partitioned indirect model recognizes both but separates them too strongly. This article claims that a composite indirect model, which reflects basic features of the common law, can better realize constitutional rights through private law in conditions of moral pluralism: it can expose private law to constitutional rights-based and reform-oriented scrutiny without ignoring, eroding, or distorting the unique normativity of private relations and practices or their underlying values.
Bishop–Jones’ theorem and the ergodic limit set
Authors: CAVALLUCCI NICOLA 
Published: September 2024

AbstractFor a proper, Gromov-hyperbolic metric space and a discrete, non-elementary, group of isometries, we define a natural subset of the limit set at infinity of the group called the ergodic limit set. The name is motivated by the fact that every ergodic measure which is invariant for the geodesic flow on the quotient metric space is concentrated on geodesics with endpoints belonging to the ergodic limit set. We refine the classical Bishop–Jones theorem proving that the packing dimension of the ergodic limit set coincides with the critical exponent of the group.
Bounds on multiplicities of symmetric pairs of finite groups
Authors: Aizenbud Avraham , Avni Nir 
Published: September 2024

Abstract
Let

$\Gamma $

be a finite group, let

$\theta $

be an involution of

$\Gamma $

and let

$\rho $

be an irreducible complex representation of

$\Gamma $

. We bound

${\operatorname {dim}} \rho ^{\Gamma ^{\theta }}$

in terms of the smallest dimension of a faithful

$\mathbb {F}_p$

-representation of

$\Gamma /\operatorname {\mathrm {Rad}}_p(\Gamma )$

, where p is any odd prime and

$\operatorname {\mathrm {Rad}}_p(\Gamma )$

is the maximal normal p-subgroup of

$\Gamma $

.
This implies, in particular, that if

$\mathbf {G}$

is a group scheme over

$\mathbb {Z}$

and

$\theta $

is an involution of

$\mathbf {G}$

, then the multiplicity of any irreducible representation in

$C^\infty \left( \mathbf {G}(\mathbb {Z}_p)/ \mathbf {G} ^{\theta }(\mathbb {Z}_p) \right)$

is bounded, uniformly in p.
Should we stay silent on violence? An ensemble approach to detect violent incidents in Spanish social media texts
Authors: Sharma Deepawali , Gupta Vedika , Singh Vivek Kumar , Pinto David 
Published: September 2024

AbstractThere has been a steep rise in user-generated content on the Web and social media platforms during the last few years. While the ease of content creation allows anyone to create content, at the same time it is difficult to monitor and control the spread of detrimental content. Recent research in natural language processing and machine learning has shown some hope for the purpose. Approaches and methods are now being developed for the automatic flagging of problematic textual content, namely hate speech, cyberbullying, or fake news, though mostly for English language texts. This paper presents an algorithmic approach based on deep learning models for the detection of violent incidents from tweets in the Spanish language (binary classification) and categorizes them further into five classes – accident, homicide, theft, kidnapping, and none (multi-label classification). The performance is evaluated on the recently shared benchmark dataset, and it is found that the proposed approach outperforms the various deep learning models, with a weighted average precision, recall, and F1-score of 0.82, 0.81, and 0.80, respectively, for the binary classification. Similarly, for the multi-label classification, the proposed model reports weighted average precision, recall, and F1-score of 0.54, 0.79, and 0.64, respectively, which is also superior to the existing results reported in the literature. The study, thus, presents meaningful contribution to detection of violent incidents in Spanish language social media posts.
CoAT: Corpus of artificial texts
Authors: Shamardina Tatiana , Saidov Marat , Fenogenova Alena , Tumanov Aleksandr , Zemlyakova Alina , Lebedeva Anna , Gryaznova Ekaterina , Shavrina Tatiana , Mikhailov Vladislav , Artemova Ekaterina 
Published: September 2024

AbstractWith recent advances in natural language generation, risks associated with the rapid proliferation and misuse of generative language models for malicious purposes steadily increase. Artificial text detection (ATD) has emerged to develop resources and computational methods to mitigate these risks, such as generating fake news and scientific article reviews. This paper introduces corpus of artificial texts (CoAT), a large-scale corpus of human-written and generated texts for the Russian language. CoAT spans six domains and comprises outputs from 13 text generation models (TGMs), which differ in the number of parameters, architectural choices, pre-training objectives, and downstream applications. We detail the data collection methodology, conduct a linguistic analysis of the corpus, and present a detailed analysis of the ATD experiments with widely used artificial text detectors. The results demonstrate that the detectors perform well on the seen TGMs, but fail to generalise to unseen TGMs and domains. We also find it challenging to identify the author of the given text, and human annotators significantly underperform the detectors. We release CoAT, the codebase, two ATD leaderboards, and other materials used in the paper.
Dialogue agents 101: a beginner’s guide to critical ingredients for designing effective conversational systems
Authors: Kumar Shivani , Bhatia Sumit , Aggarwal Milan , Chakraborty Tanmoy 
Published: September 2024

AbstractSharing ideas through communication with peers is the primary mode of human interaction. Consequently, extensive research has been conducted in the area of conversational AI, leading to an increase in the availability and diversity of conversational tasks, datasets, and methods. However, with numerous tasks being explored simultaneously, the current landscape of conversational AI has become fragmented. Consequently, initiating a well-thought-out model for a dialogue agent can pose significant challenges for a practitioner. Toward highlighting the critical ingredients needed for a practitioner to design a dialogue agent from scratch, the current study provides a comprehensive overview of the primary characteristics of a dialogue agent, the supporting tasks, their corresponding open-domain datasets, and the methods used to benchmark these datasets. We observe that different methods have been used to tackle distinct dialogue tasks. However, building separate models for each task is costly and does not leverage the correlation among the several tasks of a dialogue agent. As a result, recent trends suggest a shift toward building unified foundation models. To this end, we proposeUnit, a Unified dialogue dataset constructed from conversations of varying datasets for different dialogue tasks capturing the nuances for each of them. We then train a Unified dialogue foundation model, GPT-2$^{\textrm{U}}$and present a concise comparative performance of GPT-2$^{\textrm{U}}$against existing large language models. We also examine the evaluation strategies used to measure the performance of dialogue agents and highlight the scope for future research in the area of conversational AI with a thorough discussion of popular models such as ChatGPT.