bluuebunny/crossref_metadata_2025 huggingface dataset:
Water‐IQ matters as water conflicts mount
Authors: Bishop Kevin , Creed Irena F. , Friedman Kathryn Bryk
Published: June 2024

Water crises fuel conflicts that confound efforts to solve the underlying water crises. Water diplomacy is more effective at defusing such conflicts when the parties involved share at least a common understanding of the water involved. We argue that basic, but still up to date knowledge of where water is and how it moves is so important for finding common ground in water conflicts that this knowledge deserves a name of its own—the Water Intelligence Quotient or Water‐IQ. Science has advanced, and what people learn about the water cycle needs to reflect that. Two keystones of Water‐IQ are awareness of how profoundly people have influenced the water cycle and the atmospheric teleconnections that move water between geographic regions. Given the importance of evidence‐based knowledge of the water cycle when trying to overcome water conflicts and seek a basis for water cooperation, Water‐IQ knowledge needs to be spread widely.

This article is categorized under:

Human Water > Water Governance

Water and Life > Conservation, Management, and Awareness

Human Water > Water as Imagined and Represented
Role of epigenetics and alterations in RNA metabolism in leukodystrophies
Authors: Rey Federica , Esposito Letizia , Maghraby Erika , Mauri Alessia , Berardo Clarissa , Bonaventura Eleonora , Tonduti Davide , Carelli Stephana , Cereda Cristina
Published: June 2024

Leukodystrophies are a class of rare heterogeneous disorders which affect the white matter of the brain, ultimately leading to a disruption in brain development and a damaging effect on cognitive, motor and social‐communicative development. These disorders present a great clinical heterogeneity, along with a phenotypic overlap and this could be partially due to contributions from environmental stimuli. It is in this context that there is a great need to investigate what other factors may contribute to both disease insurgence and phenotypical heterogeneity, and novel evidence are raising the attention toward the study of epigenetics and transcription mechanisms that can influence the disease phenotype beyond genetics. Modulation in the epigenetics machinery including histone modifications, DNA methylation and non‐coding RNAs dysregulation, could be crucial players in the development of these disorders, and moreover an aberrant RNA maturation process has been linked to leukodystrophies. Here, we provide an overview of these mechanisms hoping to supply a closer step toward the analysis of leukodystrophies not only as genetically determined but also with an added level of complexity where epigenetic dysregulation is of key relevance.

This article is categorized under:

Regulatory RNAs/RNAi/Riboswitches > Regulatory RNA

RNA in Disease and Development > RNA in Disease

RNA in Disease and Development > RNA in Development
Conceptual Framework
Authors: Ibričević Aida
Published: June 2024

This chapter begins by defining the main theoretical problem and continues by situating it within existing scholarly literature. The conceptual framework is developed by surveying and synthesizing works from political science, human geography, anthropology, sociology and political psychology. The interdisciplinary literature review provides meaning and substance to concepts relevant to my study; forms interlinking relationships between these concepts and identifies gaps where a theoretical contribution can be made. I begin by setting my study within the larger literature on return migration, by examining the “voluntariness” of voluntary return, the specifics of post-conflict return, reintegration strategies and the sustainability of return. The following section develops a substantive definition of the diaspora concept and the third section of the chapter discusses how emotions have been neglected in the social sciences by a dominance of the rational-choice paradigm, by treating emotions as merely personal reactions and thus leaving them outside of the ‘political’ and by overemphasizing the methodological challenges involved in the study of emotions. Scholarly literature on citizenship is presented in the fourth section of the chapter. Next, emotional/affective/intimate citizenship is discussed as the theoretical nexus between citizenship and emotions by looking at how scholars so far have established this connection, primarily through the concepts of home and belonging, elaborated in the next two sections of the chapter. The final section of the chapter concludes by identifying how resolving the central theoretical problem contributes to the existing literature(s).
On the information content of explainable artificial intelligence for quantitative approaches in finance
Authors: Berger Theo
Published: June 2024

We simulate economic data to apply state-of-the-art machine learning algorithms and analyze the economic precision of competing concepts for model agnostic explainable artificial intelligence (XAI) techniques. Also, we assess empirical data and provide a discussion of the competing approaches in comparison with econometric benchmarks, when the data-generating process is unknown. The simulation assessment provides evidence that the applied XAI techniques provide similar economic information on relevant determinants when the data generating process is linear. We find that the adequate choice of XAI technique is crucial when the data generating process is unknown. In comparison to econometric benchmark models, the application of boosted regression trees in combination with Shapley values combines both a superior fit to the data and innovative interpretable insights into non-linear impact factors. Therefore it describes a promising alternative to the econometric benchmark approach.
Assessing ChatGPT’s Potential in HIV Prevention Communication: A Comprehensive Evaluation of Accuracy, Completeness, and Inclusivity
Authors: De Vito Andrea , Colpani Agnese , Moi Giulia , Babudieri Sergio , Calcagno Andrea , Calvino Valeria , Ceccarelli Manuela , Colpani Gianmaria , d’Ettorre Gabriella , Di Biagio Antonio , Farinella Massimo , Falaguasta Marco , Focà Emanuele , Giupponi Giusi , Habed Adriano José , Isenia Wigbertson Julian , Lo Caputo Sergio , Marchetti Giulia , Modesti Luca , Mussini Cristina , Nunnari Giuseppe , Rusconi Stefano , Russo Daria , Saracino Annalisa , Serra Pier Andrea , Madeddu Giordano
Published: June 2024

With the advancement of artificial intelligence(AI), platforms like ChatGPT have gained traction in different fields, including Medicine. This study aims to evaluate the potential of ChatGPT in addressing questions related to HIV prevention and to assess its accuracy, completeness, and inclusivity. A team consisting of 15 physicians, six members from HIV communities, and three experts in gender and queer studies designed an assessment of ChatGPT. Queries were categorized into five thematic groups: general HIV information, behaviors increasing HIV acquisition risk, HIV and pregnancy, HIV testing, and the prophylaxis use. A team of medical doctors was in charge of developing questions to be submitted to ChatGPT. The other members critically assessed the generated responses regarding level of expertise, accuracy, completeness, and inclusivity. The median accuracy score was 5.5 out of 6, with 88.4% of responses achieving a score ≥ 5. Completeness had a median of 3 out of 3, while the median for inclusivity was 2 out of 3. Some thematic groups, like behaviors associated with HIV transmission and prophylaxis, exhibited higher accuracy, indicating variable performance across different topics. Issues of inclusivity were identified, notably the use of outdated terms and a lack of representation for some communities. ChatGPT demonstrates significant potential in providing accurate information on HIV-related topics. However, while responses were often scientifically accurate, they sometimes lacked the socio-political context and inclusivity essential for effective health communication. This underlines the importance of aligning AI-driven platforms with contemporary health communication strategies and ensuring the balance of accuracy and inclusivity.
Thermal Conductivity of Liquid Cyclohexane, n-Decane, n-Hexadecane, and Squalane at Atmospheric Pressure up to 353 K Determined with a Steady-State Parallel-Plate Instrument
Authors: Berger Bioucas Francisco E. , Rausch Michael H. , Koller Thomas M. , Fröba Andreas P.
Published: June 2024

The present work reports experimental data on the thermal conductivity of the four hydrocarbons cyclohexane, n-decane, n-hexadecane, and squalane in the liquid state at ambient pressure up to temperatures of 353.15 K. Absolute measurements were performed with a steady-state guarded parallel-plate instrument (GPPI) with an average expanded (coverage factor k = 2) measurement uncertainty of 2 %. For the linear alkanes n-decane and n-hexadecane as well as the cyclic compound cyclohexane, the measured thermal conductivities agree with reference correlations in the literature, indicating the reliability of the technique used for the study of fluids with relatively low thermal conductivities and weak absorption of radiation. For the first time, experimental data are determined for the long-branched alkane squalane between (278 and 353) K, which cannot be accurately represented with estimation methods commonly used in the literature. In summary, the present measurement results confirm the existing database for representative linear and cyclic hydrocarbons and provide first experimental thermal conductivities for squalane.
Trust, Risk, Privacy and Security in e-Government Use: Insights from a MASEM Analysis
Authors: Gupta Parul , Hooda Apeksha , Jeyaraj Anand , Seddon Jonathan J.M. , Dwivedi Yogesh K.
Published: June 2024

Despite considerable research on the factors influencing the use of e-government, citizens are apprehensive of e-government services due to the concerns primarily related to trust, risk, security and privacy. This study presents a meta-analytic structural equation modeling (MASEM) analysis of the findings reported by 68 prior empirical studies on e-government adoption. Specifically, the model examined the direct effects of trust in government, trust in internet, perceived risk, and perceived privacy and security on e-government trust, and its impact on users’ behavioral intention to use e-government. The findings bear significant theoretical and practical implications.
Enhancing Preschool Teachers' Use of Pyramid Model Practices Through Coaching Intervention
Authors: Rakap Salih , Balikci Serife
Published: June 2024

The social-emotional development of young children has been shown to have a significant impact on their long-term success in life. The Pyramid Model is a widely recognized framework that preschool teachers can use to support socio-emotional development. The present study investigated the effects of a professional development program, including teacher training and coaching, on preschool teachers' utilization of social-emotional teaching practices associated with the Pyramid Model. Three preschool teachers and three children participated in this study, which employed a multiple baseline across behaviors design, implemented across participants. The combined training and coaching intervention had a positive impact on all participating teachers' implementation of social-emotional teaching practices. Moreover, the study established a clear correlation between increased implementation of these practices and a gradual reduction in challenging behaviors displayed by the children. The participating teachers expressed high acceptability and perceived relevance of the professional development intervention and Pyramid Model practices. The study contributes to the existing literature on supporting social-emotional development in early childhood settings and highlights the potential of professional development interventions to enhance teacher practices. Recommendations for future research and implications for practice are discussed.
Sensing of Co2+ and Cu2+ Ions Using Dimethylamino-functionalized Poly(azomethine-1,3,4-oxadiazole)s
Authors: Homocianu Mihaela , Hamciuc Elena , Hamciuc Corneliu
Published: June 2024

The ability of OxT and OxFl azomethines to recognize metal ions in THF solutions was investigated using UV-vis absorption techniques. Various metal ions, including Cd2+, Hg2+, Co2+, Sn2+, Cu2+, Ni2+, Zn2+ and Ag+, were tested. The absorption spectra revealed two distinct π-π* transition bands in the 273–278 nm and 330–346 nm wavelength ranges. Additionally, OxFl displayed an absorption peak at 309 nm, attributed to the fluorene group. Spectral titrations were used to study the fluorescence behavior in the presence of these metal ions. The results showed significant quenching with Co2+ and Cu2+ ions, while other metal ions had minimal effects on the fluorescence intensity. The quenching mechanism was further analyzed using the Stern-Volmer and Lehrer equations, and the binding constants ($${\mathrm{K}}_{\mathrm{b}}^{\mathrm{fl}}$$

K

b

fl

) were calculated using the Benesi-Hildebrand relations. The results confirm that Co2+ has a 1:2 stoichiometry and Cu2+ has a 1:1 stoichiometry, indicating the strong affinity of OxFl and OxT for these ions. The negative values of ΔG (Gibbs free energy) suggest that complex formation occurs spontaneously at room temperature.
A Vacuum Waveguide Filter Bank Spectrometer for Far-Infrared Astrophysics
Authors: Nie Rong , Filippini Jeffrey , Brooks Elyssa , Barry Peter , Connors Jake , Gradziel Marcin , Mercado Dale , Razavimaleki Vesal , Shirokoff Erik , Spencer Locke , Tramm Serena , Trappe Neil , Zemcov Michael
Published: June 2024

Traditional technologies for far-infrared (FIR) spectroscopy generally involve bulky dispersive optics. Integrated filter bank spectrometers promise more compact designs, but implementations using superconducting transmission line networks become lossy at terahertz frequencies. We describe a novel on-chip spectrometer architecture designed to extend this range. A filter bank spectrometer is implemented using vacuum waveguide etched into a silicon wafer stack. A single trunk line feeds an array of resonant cavities, each coupled to a kinetic inductance detector fabricated on an adjacent wafer. We discuss the design and fabrication of a prototype implementation, initial test results at ambient temperature, and prospects for future development.
Efficient path integral approach via analytical asymptotic expansion for nonlinear systems under Gaussian white noise
Authors: Di Matteo Alberto , Pirrotta Antonina
Published: June 2024

In this paper an efficient formulation of the Path integral (PI) approach is developed for determining the response probability density functions (PDFs) and first-passage statistics of nonlinear oscillators subject to stationary and time-modulated external Gaussian white noise excitations. Specifically, the evolution of the response PDF is obtained in short time steps, by using a discrete version of the Chapman-Kolmogorov equation and assuming a Gaussian form for the conditional response PDF. Next, the technique involves proceeding to treating the problem via an analytical asymptotic expansion procedure, namely the Laplace’s method of integration. In this manner, the repetitive double integrals involved in the standard implementation of the PI approach are evaluated in a closed form, while the response and first-passage PDFs are obtained by mundane step-by-step application of the derived approximate analytical expression. It is shown that the herein proposed formulation can drastically decrease the associated computational cost by several orders of magnitude, as compared to both the standard PI technique and Monte Carlo solution (MCS) approach. A number of nonlinear oscillators are considered in the numerical examples. Notably, for these systems both response PDFs and first-passage probabilities are presented, whereas comparisons with pertinent MCS data demonstrate the efficiency and accuracy of the technique.
Improving accuracy of code smells detection using machine learning with data balancing techniques
Authors: Khleel Nasraldeen Alnor Adam , Nehéz Károly
Published: June 2024

Code smells indicate potential symptoms or problems in software due to inefficient design or incomplete implementation. These problems can affect software quality in the long-term. Code smell detection is fundamental to improving software quality and maintainability, reducing software failure risk, and helping to refactor the code. Previous works have applied several prediction methods for code smell detection. However, many of them show that machine learning (ML) and deep learning (DL) techniques are not always suitable for code smell detection due to the problem of imbalanced data. So, data imbalance is the main challenge for ML and DL techniques in detecting code smells. To overcome these challenges, this study aims to present a method for detecting code smell based on DL algorithms (Bidirectional Long Short-Term Memory (Bi-LSTM) and Gated Recurrent Unit (GRU)) combined with data balancing techniques (random oversampling and Tomek links) to mitigate data imbalance issue. To establish the effectiveness of the proposed models, the experiments were conducted on four code smells datasets (God class, data Class, feature envy, and long method) extracted from 74 open-source systems. We compare and evaluate the performance of the models according to seven different performance measures accuracy, precision, recall, f-measure, Matthew’s correlation coefficient (MCC), the area under a receiver operating characteristic curve (AUC), the area under the precision–recall curve (AUCPR) and mean square error (MSE). After comparing the results obtained by the proposed models on the original and balanced data sets, we found out that the best accuracy of 98% was obtained for the Long method by using both models (Bi-LSTM and GRU) on the original datasets, the best accuracy of 100% was obtained for the long method by using both models (Bi-LSTM and GRU) on the balanced datasets (using random oversampling), and the best accuracy 99% was obtained for the long method by using Bi-LSTM model and 99% was obtained for the data class and Feature envy by using GRU model on the balanced datasets (using Tomek links). The results indicate that the use of data balancing techniques had a positive effect on the predictive accuracy of the models presented. The results show that the proposed models can detect the code smells more accurately and effectively.
Occurrence and Consequences of Matrix Effects in Simultaneous Multi-class LC-MS/MS Determination of Pesticides, Pharmaceuticals and Perfluoroalkylsubstances in Different Types of Groundwater
Authors: Keršňáková Zuzana , Lemak Ivana , Bajtoš Peter , Vabcová Jana , Hrouzková Svetlana
Published: June 2024

Matrix effects are a recent remarkable feature in quantitative LC-MS/MS analysis. In this work, the matrix effects of a multiclass mixture of 46 analytes - pesticides, pharmaceuticals and perfluoroalkylsubstances in different types of natural groundwater were studied. Groundwater samples were spiked with different standards from different chemical groups and determined by direct injection and liquid chromatography coupled to tandem mass spectrometry. Matrix effects were assessed by matrix factors calculated using the slope ratio technique. Groundwater samples were sampled in different boreholes in several places in Slovakia. The relationship with the various detected inorganic parameters was investigated and discussed. Most of the studied analytes showed negative matrix effects. Some analytes showed weak negative or positive matrix effects. The results show that average matrix factors obtained from different sampling sites are not a reliable tool and matrix effects need to be monitored depending on the sampling location. Only weak or no correlation of the matrix factors with the determined inorganic parameters was found. Geochemical composition of boreholes samples was determined and the differences in the macrochemical composition of the samples was evaluated. Model samples of ultrapure water enriched with NaCl, Na2CO3 and NaNO3 at various concentration levels were tested and the matrix effects were not observed. Other content of sample than cations Na+ were responsible for the matrix effects. It was found that the most affected compounds are sulfamethoxazole, sulfadiazine, metamitron, chloridazon and also caffeine. The results show that the detailed study is suitable as a tool for a deeper understanding of matrix effects in different types of groundwater. The proper ground water sample must be selected for reliable results of quantitative analysis.

Graphical Abstract
Silently Navigating Ethical Paradoxes in the Israel-Hamas Conflict: A Short Note
Authors: Bekerman Zvi
Published: June 2024

I embark on the writing of this short note not as an expert in ethics or a seasoned war analyst but rather as an involved observer nudged into the spotlight by a colleague’s overestimation of my insight into the Israel–Hamas conflict. I approach this task with scepticism yet hoping to morph it into a form of therapy. My own therapy, a means to break the shackles of silence that have gripped not only myself but, I suspect, many others in Israel.
Examining the elements of culturally relevant pedagogy captured and missed in a measure of high-quality mathematics instruction
Authors: Thomas Casedy Ann , Berry III Robert Q. , Sebastian Rose
Published: June 2024

Mathematics instruction is not race or culture neutral. For students who have been historically marginalized in mathematics classrooms, high-quality mathematics instruction, instruction that helps students build conceptual understanding, on its own might not be enough to disrupt inequities. These students might also need instruction that is culturally relevant, with teachers who demonstrate cultural competence, build critical consciousness, and support student learning. Our goal in this study was to understand which components of culturally relevant pedagogy (CRP) are captured and which are missed in a typical U.S. framework of high-quality mathematics instruction. To find the overlaps and gaps, we analyzed the mathematics lessons of three elementary teachers through both the lens of CRP and the Mathematics-Scan, a mathematics observation tool. We found the strongest overlap between the two frameworks in the patterns of strengths and weaknesses in the teachers’ lessons. When the teachers were delivering high-quality instruction, they were also often supporting students’ learning or showing cultural competence. When the teachers were delivering lower quality instruction, they were also often missing opportunities to enact CRP. At the same time, key elements of CRP including linguistic support for students, high expectations, critical consciousness, and nuances within cultural competence, were missed by the high-quality instruction framework. High-quality instruction was the foundation for CRP in the teachers’ classrooms, but CRP was more than just high-quality instruction. We conclude with recommendations for increasing the alignment between the frameworks and implications for international educators also grappling with equity in their own frameworks of mathematics instruction.
Proximal risk pathways of momentary alcohol urges and use: differences based on suicidal ideation history
Authors: Ammerman Brooke A. , Jacobucci Ross
Published: June 2024

Despite alcohol use being a proximal risk factor for suicidality, there have been limited examinations of alcohol use risk pathways at the momentary level among those at elevated suicide risk. Thus, we aimed to investigate risk factors relevant to predicting alcohol use experiences among those with and without a history of suicidal ideation. Data from 51 participants with a probable alcohol or substance use disorder across 21 days of ecological momentary assessment was utilized. Participants reported relevant risk factors (i.e., affect, thwarted belongingness, perceived burdensomeness) and alcohol use experiences (i.e., urges, use) four times per day. Group-level analyses examining differences in momentary associations between risk factors and alcohol use experiences based on suicidal ideation history did not detect group differences in predicting alcohol use, but group differences emerged for concurrent and prospective prediction of alcohol urges. Individual-level analyses demonstrated heterogeneity in momentary associations between risk factors, alcohol urge, alcohol use, and suicidal thinking. Together, results demonstrate the role of negative emotion, thwarted belongingness, and perceived burdensomeness in understanding momentary alcohol use experiences. Findings also highlight the complexity of, and significant heterogeneity in, the alcohol use experience among those who have experienced suicidal ideation.
Economic Development and Adolescent Wellbeing in 139 Countries
Authors: Marquez Jose , Casas Ferran , Taylor Laura , De Neve Jan-Emmanuel
Published: June 2024

There is a positive association between the level of economic development and national levels of overall life satisfaction (OLS) in the adult population, with decreasing marginal returns. However, research shows no association in early adolescence and a negative association in middle adolescence. We hypothesize that this is due to the exclusion of low-income countries, where adolescent wellbeing is rarely collected. 2015–2019 Gallup World Poll data from 139 countries in middle adolescence (age 15–17; n 36,907) were analysed using linear regression to study the association between country levels of economic development and OLS, positive emotions (PE), and negative emotions (NE), and how this varies across economic development levels, and gender. Variations across economic development levels were compared with those observed in the adult population. Log per-capita GDP is positively associated with OLS and PE, although in high-income countries no association is observed for PE, and among females for OLS. For NE, a negative association is observed in lower-income countries and a positive association in higher-income countries. In this age group (age 15–17), the log per-capita GDP – OLS association is stronger in lower-income countries than in higher-income countries, but this pattern reverses with age in adulthood. A nuanced relationship exists between economic development and adolescent wellbeing, which varies across measures, levels of economic development, gender, and age -including notable differences compared to adults. Our study highlights the need for improving child and adolescent wellbeing data worldwide, especially in lower-income countries, to better understand how best to support wellbeing globally.
Design of an on-chip wavelength conversion device assisted by an erbium-ytterbium co-doped waveguide amplifier
Authors: Zhou Chen , He Xiwen , Xiao Mingyue , Ma Deyue , Chen Weibiao , Zhou Zhiping
Published: June 2024

In current documented studies, it has been observed that wavelength converters utilizing AlGaAsOI waveguides exhibit suboptimal on-chip wavelength conversion efficiency from the C-band to the 2 μm band, generally falling below −20.0 dB. To address this issue, we present a novel wavelength conversion device assisted by a waveguide amplifier, incorporating both AlGaAs wavelength converter and erbium-ytterbium co-doped waveguide amplifier, thereby achieving a notable conversion efficiency exceeding 0 dB. The noteworthy enhancement in efficiency can be attributed to the specific dispersion design of the AlGaAs wavelength converter, which enables an upsurge in conversion efficiency to −15.54 dB under 100 mW of pump power. Furthermore, the integration of an erbium-ytterbium co-doped waveguide amplifier facilitates a loss compensation of over 15 dB. Avoiding the use of external optical amplifiers, this device enables efficient and high-bandwidth wavelength conversion, showing promising applications in various fields, such as optical communication, sensing, imaging, and beyond.

Graphical Abstract
GATA2 deficiency: a mystery myelodysplasia
Authors: Shoaib Raqiya , Pinckney Ashley , Gawash Ahmed
Published: June 2024

GATA2 deficiency, arising from mutations in the GATA2 gene, is a rare genetic disorder with profound implications for hematopoiesis, immune function, and overall health. This case report provides a comprehensive exploration of the clinical manifestations, diagnostic challenges, and management of GATA2 deficiency, emphasizing the importance of early recognition and specialized care. A 55-year-old female presented with a complex clinical presentation that evolved from myalgias into a syndrome of symptoms, including fever, chest pain, dyspnea, and profound weakness. The diagnostic journey involved recurrent admissions, a delay in diagnosis, and the consideration of various differential diagnoses, reflecting the elusive nature of GATA2 deficiency. Pulmonary involvement, hematologic abnormalities, and the patient’s transfer to a specialized center further highlighted the multifaceted aspects of this disorder. This case underscores the diagnostic challenges and clinical heterogeneity of GATA2 deficiency. It emphasizes the need for a high index of suspicion, early diagnosis, and specialized care. The elusive nature of the disorder, pulmonary involvement, and the emergence of hematologic abnormalities exemplify the complexity of GATA2 deficiency. The case report advocates for enhanced awareness, early detection, and the importance of specialized expertise in managing this rare genetic condition.
Importance of a Lake-Wetland Complex for a Resilient Walleye Fishery
Authors: Cutler Logan M. , Chipps Steve R. , Blackwell Brian G. , Coulter Alison A.
Published: June 2024

Wetlands serve as unique habitats that can support high biodiversity. Large-scale loss of wetland habitats can threaten important linkages between lake and wetland habitats that could affect diversity and growth of aquatic organisms. In this study, we compare prey diversity and abundance as well as Walleye (Sander vitreus) diets and condition in a large glacial lake (Lake Kampeska, South Dakota) with a connected wetland to better understand seasonal changes in the benefits provided by each habitat. We examined seasonal differences (spring, summer, and fall) through two years (summer 2021 through fall 2022) between the habitats using prey fish catch per unit effort, richness, Shannon diversity, and Bray–Curtis dissimilarity as well as Walleye relative weight, percent of empty stomachs, diet weight, stomach fullness, diet energy, and diet taxa importance. The prey fish community was more diverse and abundant in the wetland, and Walleye consumed more prey (by weight) in the wetland during all seasons except spring. Wetland reconnection can be a tool for managers to improve water quality while providing seasonal habitat needs for fish. Additionally, the diversity of prey resources provided by wetlands, many of which are unique, support resilience in the face of ecological change. Protection of wetlands may be critical for maintaining healthy and resilient fisheries into the future.
The things students don’t say: theorising Narrative Identity to understand non-traditional students’ experiences in higher education
Authors: Tilley Myfanwy
Published: June 2024

A persistent challenge for Australian higher education policymakers and researchers has been to understand why policies and practices have met with limited success in widening the participation and attainment of non-traditional students. This paper explores theorising Narrative Identity as a constructive methodological framework for understanding non-traditional students’ experiences in higher education. Using this approach, I critically analyse the contrasting experiences of three non-traditional students who successfully transitioned to university via an enabling program but who had significantly different (and unanticipated) levels of engagement and success in their studies. ‘Transformation’ emerged as a recurring theme in students’ perceptions of becoming academically capable students. Applying a social constructionist lens, I explore the intersections and interactions between discourses of disadvantage and transformation within the context of neoliberal higher education structural discourses. Interview data conveys students’ changing values and behaviours, revealed in their rejection of prior ‘not capable’ identities and performance of their new ‘capable student’ identity. Students’ understandings of self provide insights relevant to the sustainability of their ‘capable student’ identity and, therefore, the quality of their engagement and success. The paper concludes with a consideration of Australian higher education policy and urges greater consideration of identity challenges faced by non-traditional HE students.
Myco-remediation of synthetic dyes: a comprehensive review on contaminant alleviation mechanism, kinetic study and toxicity analysis
Authors: Upadhyay R. , Przystaś W. , Dave B.
Published: June 2024

A strong economic foundation can be achieved by the growth of a number of businesses, including food, paper, clothes, leather, and textiles. However, because of improper waste management, industrialization and modernization have resulted in the massive disposal of water effluent laden with harmful substances like dyes and heavy metals, which has negatively impacted the ecosystem. A new green technology called myco-remediation has emerged to battle harmful toxins while promoting sustainable development effectively and economically. This review employed enzymatic degradation, biosorption, and their influencing parameters for optimization in order to highlight the invaluable potential of fungal bioremediation for dye degradation. Current perspectives on enzyme immobilization techniques and kinetic studies of dye removal have been reviewed, which can aid in the selection of quick and effective removal processes. This research offers new insight into a criterion that is often overlooked in favor of dye decolorization efficiency: the toxicity assessment of pure dye and post-process metabolites produced following myco-remediation. Our attention has been directed towards toxicity analysis at many levels, including genotoxicity, phytotoxicity, and zoo-toxicity. This is important to keep in mind when considering the extensive implications of myco-remediation for the recycling and reuse of industrial effluent. Enzyme engineering and omics technologies have been highlighted as potential future developments.
Enabling active visitor management: local, short-term occupancy prediction at a touristic point of interest
Authors: Bollenbach Jessica , Neubig Stefan , Hein Andreas , Keller Robert , Krcmar Helmut
Published: June 2024

After the temporary shock of the Covid-19 pandemic, the rapid recovery and resumed growth of the tourism sectors accelerates unsustainable tourism, resulting in local (over-)crowding, environmental damage, increased emissions, and diminished tourism acceptance. Addressing these challenges requires an active visitor management system at points of interest (POI), which requires local and timely POI-specific occupancy predictions to predict and mitigate crowding. Therefore, we present a new approach to measure visitor movement at an open-spaced, and freely accessible POI and evaluate the prediction performance of multiple occupancy and visitor count machine learning prediction models. We analyze multiple case combinations regarding spatial granularity, time granularity, and prediction time horizons. With an analysis of the SHAP values we determine the influence of the most important features on the prediction and extract transferable knowledge for similar regions lacking visitor movement data. The results underline that POI-specific prediction is achievable with a moderate relation for occupancy prediction and a strong relation for visitor count prediction. Across all cases, XGBoost and Random Forest outperform other models, with prediction accuracy increasing as the prediction time horizon shortens. For effective active visitor management, combining multiple models with different spatial aggregations and prediction time horizons provides the best information basis to identify appropriate steering measures. This innovative application of digital technologies facilitates information exchange between destination management organizations and tourists, promoting sustainable destination development and enhancing tourism experience.
“It’s Time to see What I Can Do”: A Mixed-Methods Investigation into Trajectories of Resilience in Adolescents during the COVID-19 Pandemic
Authors: Fradley K , Bennett K. M. , Ellis R. E. , Gibson-Miller J. , Bentall R. P. , Levita L.
Published: June 2024

There is a concern that adolescent mental well-being and resilience has been adversely affected by the COVID-19 pandemic. Consequently, the aim of the current investigation was to track adolescents’ resilience from the initial months of the pandemic (T1) to approximately two years later (T2) using both qualitative and quantitative methods. Through interviews, thirty-one adolescents narrated their COVID-19 experiences and reflected on their mental well-being across this timespan. Using these accounts, we identified four groups of adolescents exhibiting one of the following trajectories of resilience: (1) Enduring resilience, (2) Reaching resilience, (3) Declining resilience and (4) Enduring non-resilience. Our findings revealed that most adolescents were able to maintain or develop good resilience on prolonged exposure to COVID-19 adversity (trajectories 1 and 2). This finding is contrary to the prevailing notion that the majority of adolescents’ mental well-being and hence resilience was adversely impacted by COVID-19 in the short and long term. Further qualitative analysis identified key factors that contributed to maintaining and developing greater levels of resilience during the pandemic: quality of friendships, quality of family relationships and regaining a sense of control. Lastly, we found a lack of congruence between quantitative and qualitative measures of mental well-being and resilience, suggesting that they might tap into different constructs/experiences. Significantly, our findings highlight that the majority of teens showed adaptive resilience during the pandemic and highlight the need for further longitudinal qualitative and quantitative research to assess both adaptive and maladaptive impacts of adversity on the adolescents’ mental well-being and resilience.
On the Computation of the Cohomological Invariants of Bott–Samelson Resolutions of Schubert Varieties
Authors: Franco Davide
Published: June 2024

Let $$X\subseteq G/\mathcal {B}$$

X
⊆
G
/
B

be a Schubert variety in a flag manifold and let $$\pi : \tilde{X} \rightarrow X$$

π
:

X
~

→
X

be a Bott–Samelson resolution of X. In this paper, we prove an effective version of the decomposition theorem for the derived pushforward $$R \pi _{*} \mathbb {Q}_{\tilde{X}}$$

R

π

∗

Q

X
~

. As a by-product, we obtain recursive procedure to extract Kazhdan–Lusztig polynomials from the polynomials introduced by Deodhar [7], which does not require prior knowledge of a minimal set. We also observe that any family of equivariant resolutions of Schubert varieties allows to define a new basis in the Hecke algebra and we show a way to compute the transition matrix, from the Kazhdan–Lusztig basis to the new one.
Transdisciplinary approaches assessing unmanaged urban green spaces reveal benefits for biodiversity and people
Authors: Engemann Kristine , Breed Christina , Brom Peta , Pasgaard Maya
Published: June 2024

Rapid urbanization is projected for African cities at the cost of urban green space, which could jeopardize biodiversity and human benefits. Studies focusing specifically on human–green space relationships in the Global South are lacking, and the validity of extrapolating results from studies in the Global North remains questionable and cannot provide local context-specific design solutions. This study combines methods and perspectives from ecology and human geography with landscape design to better understand the benefits for biodiversity and people derived from unmanaged green spaces in the City of Tshwane, South Africa. Based on empirical data from two unmanaged green space areas in disadvantaged communities, we identify benefits for biodiversity and people and define guidelines for inclusive trans-disciplinary interventions. We combine information from a vegetation survey, a community survey of 200 respondents and a rapid assessment of multifunctional benefit provision to formulate in holistic landscape design proposals. We show that the sites have biodiversity value and provide habitat for > 169 different plant species, including protected species, and smaller wildlife. Residents use the spaces for utility, passive and active leisure, and > 76% of residents benefit from the use of these spaces. However, the integrity and provision of benefits from green spaces are threatened by pollution, safety concerns, biological invasions, and land conversion. Context-specific designs could be developed by merging methods across disciplines and involving local stakeholders to integrate the multifunctionality of socioecological benefits into landscape interventions. Collaboration across ecology, human geography and landscape design generates multifunctional perspectives of unmanaged green spaces that consider benefits for biodiversity and disadvantaged communities.
Multiple indicators-based assessment of rural food security status in landslide-prone areas of Southern Ethiopia
Authors: Tadesse Lemma , Uncha Abera , Toma Thomas
Published: June 2024

Landslide hazards significantly threaten rural communities, impacting various aspects of livelihoods, including food security. The Gamo Highlands in southern Ethiopia is vulnerable to landslide hazards. Therefore, this research aims to investigate the effect of landslide hazards on rural households’ food security status in the Gacho Baba district, Gamo Highlands, southern Ethiopia. The study employed a mixed approach, to collect and analyze data collected from 289 households, community leaders, and early warning and food security experts. Purposive and multistage sampling techniques were deployed. Both descriptive and inferential statistics were used to analyze the data. Household Food Insecurity Access Scale (HFIAS), Food Consumption Score (FCS), and Reducing Coping Strategies Index (RCSI) were food in/security indicators used. The HFIAS reveals significant worries regarding stable access and availability of food, with 62% of sample households categorized as mildly, moderately, and severely food-insecure. FCS indicates prevalent challenges in achieving adequate food consumption levels among the surveyed households, with a significant portion falling into the poor consumption category (51.3%). while the investigation of coping strategies using RCSI categorized (53.3%) of study samples into high coping strategies. The study also reveals varying levels of awareness and preparedness among households, with a significant proportion expressing uncertainty about landslide occurrence and prevention mechanisms. The findings underscore the need for targeted educational and awareness initiatives, as well as comprehensive risk reduction strategies, to enhance household resilience and safeguard food security in landslide-prone areas.
Comparing the performance of machine learning models for predicting the compressive strength of concrete
Authors: Loureiro Arthur Afonso Bitencourt , Stefani Ricardo
Published: June 2024

This work aimed to investigate and compare the performance of different machine learning models in predicting the compressive strength of concrete using a data set of 1234 compressive strength values. The predictive variables were selected based on their relevance using the SelectKBest method, resulting in an analysis of eight and six predictive variables. The evaluation was conducted through linear correlation studies via simple linear regression and non-linear correlation studies using support vector regression (SVR), random forest (RF), gradient boosting (GB), and artificial neural networks (ANN). The results showed a coefficient of determination (R2) = 0.897 and a root mean square error (RMSE) = 6.535 MPa for SVR, R2 = 0.885 and RMSE = 5.437 MPa for GB, R2 = 0.868 and RMSE = 5.859 MPa for GB and R2 = 0.894 and RMSE = 5.192 MPa for ANN, all for test set and eight predictor variables. The comparison between the machine learning methods revealed significant differences. For instance, ANN stood out with a higher R2 value, demonstrating its remarkable ability to explain the variability in the data. ANN also showed the lowest RMSE value, indicating notable accuracy in the predictions. Although ANN has demonstrated higher performance, GB shows a closer performance, which no differences from a practical application. The choice between these approaches depends on considerations regarding the balance between explainability and accuracy. While GB provides a more in-depth understanding of the relationship between variables, ANN stands out for the accuracy of its predictions.
Implementation of multifaceted diagnostic stewardship for Clostridioides difficile infection during the COVID-19 pandemic at a small Japanese hospital
Authors: Sasaki Yasuhiro , Yano Masataka , Umehara Ayumi , Tagashira Yasuaki
Published: June 2024

Objective:

Clostridioides difficile infection (CDI) is a common, healthcare-associated infection. However, in Japan, testing for CDI is infrequent, suggesting that its incidence may be underestimated. This study aimed to examine the implementation of a multifaceted, diagnostic stewardship (DS) for CDI in a small Japanese hospital during the coronavirus 2019 pandemic.

Design:

Before-after study.

Setting:

A small Japanese community hospital.

Participants:

Healthcare workers including physicians, nurses, and pharmacists.

Interventions:

A multifaceted intervention including (1) the addition of CD testing criteria to the hospital guidelines; (2) provision of a tutorial on CD testing to physicians, nurses, and pharmacists; (3) assessment by clinical pharmacists and nurses of the need for CD testing in patients with nosocomial diarrhea and issuance of recommendations for CD testing to physicians; (4) reporting of data on the CD testing rate and CDI incidence in the study center.

Results:

The CD testing rate increased before the pandemic (+0.16/10,000 patient-days (PD); P = .28), decreased significantly during the pandemic (−0.79/10,000 PD; P = .02), and then increased significantly immediately after the implementation of the intervention (+29.6/10,000 PD; P < .01). Similarly, the CDI incidence increased significantly before the pandemic (+0.26/10,000 PD; P = .02) and decreased significantly during the pandemic (−0.49/10,000 PD; P = .01). Implementation of the intervention resulted in an immediate and significant increase in the CDI incidence (+6.2/10,000 PD; P < .01).

Conclusion:

Multifaceted DS involving multidisciplinary specialists was effective in improving CD testing, suggesting that appropriate testing can contribute to diagnosing CDI accurately.
Pet Owners Risk Perception and Risk Communication in Disasters in Developing Countries
Authors: Moslehi Shandiz , Narimani Sajjad
Published: June 2024

Disasters can cause great physical and financial damage to pet owners in developing countries. These effects lead to severe psychological side effects on individuals and families. With the tendency of families to keep pets in these countries, many challenges have arisen regarding how to manage these pets before, during, and after disasters. Therefore, mitigation, prevention, and preparedness measures for these families should be prioritized in the disaster management cycle to minimize psychological effects such as posttraumatic stress disorder (PTSD) after losing pets.