bluuebunny/crossref_metadata_2025_split huggingface dataset:
"Challenges and future in deep learning for sentiment analysis: a comprehensive review and a proposed novel hybrid approach"
Authors: Islam Md. Shofiqul , Kabir Muhammad Nomani , Ghani Ngahzaifa Ab , Zamli Kamal Zuhairi , Zulkifli Nor Saradatul Akmar , Rahman Md. Mustafizur , Moni Mohammad Ali 
Published: February 2024

AbstractSocial media is used to categorise products or services, but analysing vast comments is time-consuming. Researchers use sentiment analysis via natural language processing, evaluating methods and results conventionally through literature reviews and assessments. However, our approach diverges by offering a thorough analytical perspective with critical analysis, research findings, identified gaps, limitations, challenges and future prospects specific to deep learning-based sentiment analysis in recent times. Furthermore, we provide in-depth investigation into sentiment analysis, categorizing prevalent data, pre-processing methods, text representations, learning models, and applications. We conduct a thorough evaluation of recent advances in deep learning architectures, assessing their pros and cons. Additionally, we offer a meticulous analysis of deep learning methodologies, integrating insights on applied tools, strengths, weaknesses, performance results, research gaps, and a detailed feature-based examination. Furthermore, we present in a thorough discussion of the challenges, drawbacks, and factors contributing to the successful enhancement of accuracy within the realm of sentiment analysis. A critical comparative analysis of our article clearly shows that capsule-based RNN approaches give the best results with an accuracy of 98.02% which is the CNN or RNN-based models. We implemented various advanced deep-learning models across four benchmarks to identify the top performers. Additionally, we introduced the innovative CRDC (Capsule with Deep CNN and Bi structured RNN) model, which demonstrated superior performance compared to other methods. Our proposed approach achieved remarkable accuracy across different databases: IMDB (88.15%), Toxic (98.28%), CrowdFlower (92.34%), and ER (95.48%). Hence, this method holds promise for automated sentiment analysis and potential deployment.
Integration of Measurement-Based Care for Youth Depression and Suicidality Using VitalSign6
Authors: Mitchell Tarrah B. , Wakefield Sarah M. , Rezaeizadeh Afsaneh , Minhajuddin Abu , Pipes Ronny , Mayes Taryn L. , Elmore Joshua S. , Trivedi Madhukar H. 
Published: February 2024

AbstractDepression and suicidality are prevalent in youth and are associated with a range of negative outcomes. The current study aimed to evaluate a measurement-based care (MBC) software (VitalSign6) tool to improve the screening and treatment of depression and suicidality in youth aged 8–17 years within a rural, underserved population. To assess for depression and suicidality, the Patient Health Questionnaire-2 was administered as an initial screen, and the Patient Health Questionnaire-9 Modified for Adolescents (PHQ-9-A) was administered if the initial screen was positive. Data were collected at medical clinics over one year, and descriptive statistics and t-tests or Wilcoxon-Mann-Whitney tests were conducted. A total of 1,984 youth were initially screened (mean age of 13 years; 51.6% female); 24.2% screened positive for depression, and 14.9% endorsed suicidality. Of those who screened positive, the mean PHQ-9-A score was 12.8; 66.9% had PHQ-9-A scores in the moderate to severe range, and 44.2% endorsed suicidality. Almost half of the youth who screened positive for depression had at least one follow-up assessment, and about one quarter achieved remission 4 months after initial screening. Adolescents (12–17 years) had higher PHQ-9-A scores, higher suicidality, and more follow-up assessments than younger youth (8–11 years). Younger youth had higher rates of remission. The widespread use of MBC was feasible in this setting. It is important to utilize MBC to identify and treat youth with depression and suicidality and to do so in younger populations to improve their trajectory over time; VitalSign6 is one tool to help achieve these goals.
Taxonomy of competence models based on an integrative literature review
Authors: Mikhridinova Nargiza , Wolff Carsten , Van Petegem Wim 
Published: February 2024

AbstractAn individual competence is one of the main human resources, which enables a person to operate in everyday life. A competence profile, formally captured and described as a structured model, may enable various operations, e.g., a more precise evaluation and closure of a training gap. Such application scenarios supported by information systems are particularly compelling for the era of digitalisation, although research on adequate models capturing competence profiles is still lacking; moreover, no research was revealed synthesizing models of competence, enabling operationalisation possibilities. To fulfil this gap, current research develops a classification of competence models in the form of taxonomy, derived from operational characteristics of competence constructs. Given conceptual fuzziness of the competence term and complex, interdisciplinary scope of the study, the research method follows integrative literature review principles: results of an extensive search conducted in three iterations were critically analysed and further synthesized in the form of taxonomy. This critical analysis was performed based on an overview of twenty-four competence models with a lens of working definitions of competence framework and model concepts. As a result, all three outcomes highlight the power of competence models: (1) the overview summarises models’ development methods, operationalisation, and purposes in a specific application domain, while (2) working definitions and (3) the taxonomy aim at overcoming a conceptual ambiguity of competence concepts. In addition, the presented taxonomy may serve as a knowledge base or a decision support tool on competence model selection when it comes to development of a competence management tool.
The effect of AI-powered chatbots in social studies education
Authors: Yeti̇şensoy Okan , Karaduman Hıdır 
Published: February 2024

AbstractThe aim of this research is to investigate the educational potential of AI-powered chatbots in Social Studies learning-teaching processes. The study was conducted using embedded design, evaluated within the framework of mixed methods research. The study group consists of 78 6th-grade students studying in three different classes, along with one teacher who implemented the practices and guided the process. During the experimental phase of the study, lessons in the experimental group were taught by the practitioner teacher using an AI-powered chatbot named “SosyalciBot”. Meanwhile, lessons in two control groups were taught following the constructivist approach. At the end of the process, it was determined that the experimental group students’ post-test and permanency test scores were significantly higher than the control group students’ scores in both post-test and permanency test. In the semi-structured interviews, both students and the practitioner teacher provided positive evaluations of the pedagogical and design features of the chatbot, indicating that these features positively impacted the learning-teaching process. They also identified some shortcomings while offering suggestions for improvement. Based on the study findings, it is evident that chatbots have a high potential to contribute to Social Studies education. However, to fully harness this potential and achieve optimal effectiveness, further advancements and refinements in chatbot technology are required. At this point, it is recommended to conduct theoretical or applied studies focusing on developing chatbots with high communication capacity and explore innovative and constructive ideas regarding the integration of chatbots into educational environments.
“This is Where the Care Can Step Up”: A Typology of Nurturing Pedagogies in Primary Schools Serving Low-Income Communities During COVID-19 Closures
Authors: Gleasure S. , Devine D. , Martinez Sainz G. , Sloan S. , Crean M. , Moore B. , Symonds J. 
Published: February 2024

Abstract
All schools possess a duty of care towards their students. However, this duty of care falls unevenly across schools, with those serving low-income communities often responding to the material and psychological effects of poverty as a priority. This duty of care for such schools was placed into stark relief during the period of COVID-19 school closures, when structural inequalities in society became particularly pronounced. Previous research has drawn distinctions between different forms of caring enacted in schools serving low-income communities. These range from practices centred on children’s academic learning to those more concerned with children’s welfare and well-being—which, for the purposes of this paper, we term as academic nurturing and affective nurturing respectively. Others recognise the need for schools in low-income communities to perform a dual role and engage in both forms of nurturing simultaneously—which we term as critical nurturing. This paper presents findings based on case studies from three designated disadvantaged primary schools in Ireland during pandemic-related closures. It draws on interviews from the Children’s School Lives longitudinal study with the teachers, principals, and families of four Junior Infant children (typically aged four to five years). Our findings suggest a typology of nurturing pedagogies, with academic and affective nurturing emphasised to varying degrees across our three schools during this period. Narratives from interviewees also demonstrate the central role of school culture and leadership in achieving critical nurturing, with significant social justice implications for the education of children in schools serving low-income communities.
Decarbonization of waste management practices and GHG accounting for energy transition: evidence from European electricity corporations’ reporting
Authors: Di Vaio Assunta , Van Engelenhoven Elisa , Chhabra Meghna , Garofalo Antonio 
Published: February 2024

AbstractThis study advances the understanding about the waste management practices adopted by the electricity sector for meeting the energy transition. Specifically, through the institutional, stakeholder, and legitimacy theory lens, it investigates the decarbonization practices in 11 major electricity producers in Europe trying to understand their sincere concern for enhanced performance and transparency. This study analyzes the content of non-financial disclosures shown by 90 reports, that is 64 sustainability reporting and 26 integrated reporting published between 2015 and 2022. Hence, this study seeks to clarify the linkages between waste management for emissions reduction, GHG accounting and sustainability reports through which the corporations seek legitimacy from stakeholders. The results highlight the commitment of electricity corporations for energy transition using green technologies and renewable energy sources to decarbonize the waste practices. However, they underline the absence of quantitative evidence in the SR for the evaluation of initiatives impact and the reduction of GHG emissions. To the best of our knowledge, this is the first study that conceptualizes the linkages between waste decarbonization for energy transition and the accounting systems i.e. GHG accounting and reporting in the electricity sector towards a cleaner production.
Reconstruction of f(R) Gravity from Cosmological Unified Dark Fluid Model
Authors: Elkhateeb Esraa Ali 
Published: February 2024

AbstractIn this work, we reconstruct the cosmological unified dark fluid model proposed previously by Elkhateeb (Astrophys Space Sci 363(1):7, 2018) in the framework of f(R) gravity. Utilizing the equivalence between the scalar-tensor theory and the f(R) gravity theory, the scalar field for the dark fluid is obtained, whence the f(R) function is extracted and its viability is discussed. The f(R) functions and the scalar field potentials have then been extracted in the early and late times of asymptotically de Sitter spacetime. The ability of our function to describe early time inflation is also tested. The early time scalar field potential is used to derive the slow roll inflation parameters. Our results of the tensor-to-scalar ratio r and the scalar spectral index $$n_s$$

n
s

are in good agreement with results from Planck-2018 TT+TE+EE+lowE data for the model parameter $$n > 2$$

n
>
2

.
Synthesis, Properties, and Degradation of Poly(butylene succinate-co-sebacicate-co-salicylicate) Copolyesters
Authors: Chen Yezhong , Pan Kaibo , Mai Kaijin , Jiao jian , Zeng xiangbin , Fu Qiang , Li Jianjun 
Published: February 2024

AbstractSince monomers in backbone of poly(butylene succinate-co-adipate) (PBSA) are not entirely derived from bio-based sources, limiting its application in the face of increasingly stringent environmental policies. In this study, a novel full bio-based biodegradable random copolyester poly(butylene succinate-co-sebacicate-co-salicylicate) was successfully synthesized. Detailed investigations were conducted on the structural, mechanical, and degradation characteristics resulting from the introduction of salicylicate and sebacicate units. Introduction of salicylicate units effectively enhanced the mechanical performance. In comparison to PBSA, the tensile modulus of copolymer increased by 20.2% with 10% salicylic acid. Introduction of sebacicate units significantly altered the crystalline structure of copolymer and promote the degradation efficiency. Considering both mechanical strength and degradation efficiency, the copolyester with 2% salicylic acid and 20% sebacic acid was found to meet practical application requirements. Relative to PBSA, this copolymer demonstrated a 13.7% increase in tensile modulus and a remarkable 143.1% improvement in degradation efficiency. Importantly, this study focused on the effect of the bio-based rigid monomer salicylic acid and the soft monomer sebacic acid on the degradability of biodegradable polymers. The insights gained provide valuable guidance for tailoring the synthesis of degradable plastics to meet diverse degradation cycle requirements.
Mechanochemical preparation of nanocrystalline stannite/chatkalite composite: kinetics of synthesis and thermoelectric properties
Authors: Baláž Peter , Rajňák Michal , Kubíčková Lenka , Hudáková Mária Bali , Daneu Nina , Levinský Petr , Knížek Karel , Hejtmánek Jiří , Navrátil Jiří , Kmječ Tomáš , Džunda Robert , Achimovičová Marcela , Šestinová Oľga , Baláž Matej 
Published: February 2024

AbstractIn this study we demonstrate the use of Cu, Fe, Sn and S elemental precursors to synthesize chatkalite/stannite nanocomposite by high-energy milling in both lab-scale and industrial-scale mills. The products were characterized by XRD, SEM, HRTEM, EDX, Mössbauer spectroscopy and magnetometry. For the determination of optimum milling conditions, the magnetization data of the synthesized samples were used as output values using a Taguchi experimental design. The formation of the product proceeds via a multistep process comprising binary sulphides (SnS and CuS) formation at the beginning and chatkalite Cu6FeSn2S8/stannite Cu2FeSnS4 composite as the end products. The TEM images show tightly packed nanosized crystallites with the sizes in the range of tens of nanometers. Mössbauer study unveiled that iron is present in 3+ state instead of 2+ expected for stoichiometric phases. This discrepancy was explained by the presence of a small number of vacancies on Sn sites. Based on the thermoelectric measurements of the hot-pressed pellets, the calculated figure of merit reached a value of ZT = 0.27 at 600 K. The aim of this study is to prepare a representative of a promising class of environmentally acceptable thermoelectric materials in an environmentally sound solvent-free manner and characterize them while studying the kinetics of the reaction via magnetometry and the possibility to scale-up the solid-state synthesis process.
How important is passive sampling to explain species-area relationships? A global synthesis
Authors: da Silva Marco Aurélio Ferreira , Mendes Clarice Braúna , Prevedello Jayme Augusto 
Published: February 2024

Abstract
Context
The species-area relationship (SAR) is one of the main patterns in Ecology, but its underlying causes are still under debate. The random placement hypothesis (RPH) is the simplest one to explain the SAR: larger areas passively sample more individuals and, consequently, more species. However, it is still unclear the degree to which this null hypothesis is supported for different taxa and locations globally.

Objectives
We performed the first global synthesis on the RPH to investigate which variables mediate variation in the degree of support of this hypothesis across taxa and regions.

Methods
We conducted a review of the global literature and estimated the degree of support of the RPH. The degree of support (effect size) was inferred through the coefficient of determination of the relationship between observed (empirical) and predicted (according to the RPH) species richness. We analyzed the relationship between this effect size metric and different geographic and ecological factors.

Results
About 31% of the studies explicitly considered the RPH. From these, only 14% tested the RPH in a total of 52 independent case studies. About 42% of these case studies confirmed the RPH. The degree of support was significantly higher for plants than animals, and increased consistently with latitude for animals.

Conclusions
Passive sampling is important to determine SARs, especially for animals at higher latitudes and plants. Further tests of the RPH, which is still scarcely explored in the literature, are vital to understanding the stochastic and ecological processes underlying the SAR and to advancing Landscape Ecology.
High-resolution species distribution modelling reveals spatio-temporal variability of habitat suitability in a declining grassland bird
Authors: Crispim-Mendes Tiago , Valerio Francesco , Marques Ana Teresa , Pita Ricardo , Godinho Sérgio , Silva João Paulo 
Published: February 2024

Abstract
Context
Species distribution models (SDMs) may provide accurate predictions of species occurrence across space and time, being critical for effective conservation planning.

Objectives
Focusing on the little bustard (Tetrax tetrax), an endangered grassland bird, we aimed to: (i) characterise the drivers of the species distribution along its key phenological phases (winter, breeding, and post-breeding); and (ii) quantify spatio-temporal variation in habitat suitability across phenological phases and over the years 2005–2021.

Methods
Combining remotely sensed metrics at high temporal resolution (MODIS) with long-term (> 12 years) GPS telemetry data collected for 91 individuals at one of the species’ main strongholds within the Iberian Peninsula, we built SDMs (250 m resolution) for the species key phenological phases.

Results
The use of both dynamic and static predictors unveiled previously unknown ecological responses by little bustards, revealing a marked change in the spatial distribution of suitable habitat among phenological phases. Long-term habitat suitability trends showed considerable fluctuations, mainly in the breeding and post-breeding phases. Overall, SDM projections into the past revealed that while the species’ winter and post-breeding habitats apparently increased since 2005, suitable habitat during the species’ most critical phenological phase, breeding, apparently reduced in area over time.

Conclusions
Our findings show that matching remotely sensed data with GPS tracking data results in accurate habitat suitability predictions throughout the yearly cycle. Additionally, our findings stress the importance of quantifying habitat loss and its potential impact on little bustard decline over nearly 20 years. Spatio-temporal variations in habitat suitability are also identified in this work, which can help prioritize conservation areas, particularly the breeding areas that have remained stable over time, as this is a key requirement for little bustard lek breeding system.
Spatio-temporal changes and hydrological forces of wetland landscape pattern in the Yellow River Delta during 1986–2022
Authors: Qiu Mengqi , Liu Yanxu , Chen Peng , He Naijie , Wang Shuai , Huang Xinzi , Fu Bojie 
Published: February 2024

Abstract
Context
Estuarine wetlands provide valuable ecosystem services, but 20–78% of coastal wetlands are facing the risk of loss by the end of the century. The Yellow River Delta (YRD) wetland, one of the most productive delta areas in the world, has undergone dramatic changes under the influence of a precipitous drop of sediment delivery and runoff, coupled with the invasion of Spartina alterniflora. Monitoring the spatio-temporal patterns, thresholds, and drivers of change in wetland landscapes is critical for sustainable management of delta wetlands.

Objectives
Generate annual mapping of salt marsh vegetation in the YRD wetland from 1986 to 2022, analyze the trends of wetland patch area and landscape pattern, and explain the hydrological drivers of landscape pattern evolution.

Methods
We combined Landsat 5‒8 and Sentinel-2 images, vegetation phenology, remote sensing indices, and Random Forest supervised classification to map the typical salt marsh vegetation of the YRD. We applied piecewise linear regression to analyze YRD wetland changes and stepwise multiple linear regression to assess the impact of hydrological factors on landscape pattern.

Results
We identified three stages of landscape pattern evolution with 1997 and 2009 as critical junctures, including the rapid expansion stage, gradual decline stage, and bio-invasion stage. In the rapid expansion stage, the wetland area expanded by 70%, while the typical salt marsh vegetation (Phragmites australis) area was reduced by 25%. In the gradual decline stage, the wetland was reduced by 21% and the Phragmites australis area was reduced by 16%. In the bio-invasion stage, coverage of Spartina alterniflora expanded rapidly, with a 68-fold increase in area relative to 2009, expanding at an average rate of 344 hm2 per year.

Conclusions
Areas of total wetland, tidal flat, and Phragmites australis were significantly influenced by cumulative sediment delivery and cumulative runoff, which together explained 61.5%, 75.7% and 63.8% of their variation, respectively. Wetland and tidal flat areas increased with cumulative sediment delivery, while cumulative runoff had a weak negative effect. For Phragmites australis, cumulative runoff had a positive effect, whereas cumulative sediment delivery had a negative effect. Water resources regulation measures should be taken to prevent the degradation of wetland ecosystems, and intervention measures can be implemented during the seedling stage to control the invasion of Spartina alterniflora.