bluuebunny/crossref_metadata_2025 huggingface dataset:
Isothermal Reduction Behavior of Oxide Scale on the Surface of Hot‐Rolled Strip Steel Under Different Hydrogen Concentrations
Authors: He Shuai , Li Zhi‐Feng , Liu Xin , Liu Xu‐Ming , Wang Jun‐Sheng
Published: August 2024

The oxide scale on the surface of hot‐rolled low‐carbon steel strips is subjected to isothermal reduction in 10 vol%H2–Ar and 20 vol%H2–Ar environments to simulate the reduction process that occurs in a continuous annealing furnace. The influence of hydrogen concentration on the reduction kinetics and the microstructural evolution of the oxide scale after reduction at temperatures ranging from 450 to 850 °C for a duration of 20 min are investigated in detail. The mass changes of the oxide scale in the two gases are quantified using a thermogravimetric analyzer. This data is then employed to calculate the reduction rate constant and the apparent activation energy. To examine the microstructure and element distribution, electron probe microanalysis and energy‐dispersive spectrometry are employed. An novel approach is also undertaken to assess the reduction degree of the oxide scale by measuring surface microhardness. In the findings, it is indicated that an increase in hydrogen concentration served primarily to accelerate the reduction reaction within the temperature ranges of 450–550 and 800–850 °C. Meanwhile, the mechanism of physical transformation of oxide scale, the microstructure of reduction layer, and hydrogen concentration on reduction efficiency under different reaction stages are proposed.
Electrochemical detection of the cardiac biomarker cardiac troponin I
Authors: Qin Xiaoyun , Li Dongyang , Qin Xiaomei , Chen Fenghua , Guo Huishi , Gui Yanghai , Zhao Jianbo , Jiang Liying , Luo Dan
Published: August 2024

Acute myocardial infarction (AMI) is a major cause of cardiovascular disease‐related death. It is essential for patients with cardiovascular disease to receive an early diagnosis of AMI. The most popular technique for the early detection of AMI is the use of biosensors to monitor the concentration of pertinent biomarkers, such as cardiac troponin I (cTnI), in the blood. The electrochemical detection methods hold great promise because of their simplicity, miniaturization, ease of integration, high sensitivity, and rapid response. The prime motive of this review is to present a comprehensive understanding of the pros and cons of methodologies employed for the electrochemical approaches toward the detection of cTnI. A detailed summary is provided for the immunosensors, aptamer sensors, molecular imprinting sensors, and peptide sensors based on various affinity elements. We enumerate the modified electrode materials for electrochemical sensors as well as popular detection techniques. Furthermore, this paper reviews some recent significant advances in point‐of‐care assays for rapid, accurate detection of cTnI as a smart integrated device for home monitoring. The accumulation of knowledge about these functions will lead to new insights into and concepts for the design of portable miniature sensors for cardiovascular patients at risk of AMI. It is anticipated that the interdisciplinary collaboration can bring more enlightenment to the progress of cardiac biomarkers sensor in the future.
The Italian Agency for Development Cooperation in Jordan
Authors: Blasi Alessandra
Published: August 2024

In Jordan, the conservation and valorization of cultural heritage plays an important role in enhancing social cohesion and enriching understanding of the past, in that it addresses the identity and integrity of sites of cultural and historical interest, and works towards valorizing living heritage assets. The rehabilitation of artefacts and heritage sites, as well as strategies directed at the conservation of the urban fabric, also indirectly impact livelihoods within local communities. These actions result in increasingly appealing assets, which then attract potential visitors. This, in turn, allows for profitable, visitor-oriented activities that can boost the tourist industry. Such socio-economic connectivity provides a foundation upon which the quality of life of local residents can be improved. In the long term, it can lead to an increase in inclusivity, in the response capacity of women and children to vulnerability, the adaptability of investments and, ultimately, the development of sustainable tourism policies and strategies, based on changes in consumer preferences, which would work to bolster recovery.
Heritage Preservation in Bamiyan: Achievements 2002–21
Authors: Bouchenaki Mounir
Published: August 2024

The contribution establishes the importance of the Florence conference on Cultural Heritage in Fragile Contexts. It firstly outlines the endeavors of various international organizations for the salvation of Bamiyan’s giant Buddha statues as well as other assets of cultural heritage in the spring of 2001 and the role of the author in these initiatives. Then, it illustrates the bodies instituted by UNESCO for the management of the Bamiyan World Heritage site, which have been resumed by the above mentioned conference in Florence. Finally, it underscores the relevance of enduring capacity building for the safeguarding of cultural heritage assets, especially in fragile contexts.
Unfinished Business: The Albanese Government and Gender Equality Policy (2022–?)
Authors: Johnson Carol
Published: August 2024

This chapter focuses on Australian government policy but also provides relevant international examples. Labor’s Anthony Albanese came into office committed to making Australia a world leader in gender equality policy again. Labor pledged to complete some of the Gillard government’s agenda. The government has a particular focus on improving wages in, and training for, the “care economy”. Improving gender equality is also seen as beneficial for the economy in general. The government has made significant progress in areas such as pay equity, childcare, parental leave, housing for those fleeing domestic violence, skills and training. It is a social democratic framing that recognises issues of structural disadvantage and inequality and aimed to address them. However, the government has also been constrained by trying to bring in reforms in difficult economic times. Furthermore, the government has lacked imagination when it comes to challenging the limitations of a conventional social democratic policy framing. The experience of the Albanese government has useful lessons for governments internationally that are attempting to address the impacts of decades of neoliberalism on gender equality policy. The government also unsuccessfully tried to enshrine an innovative Indigenous Voice to parliament that would have included a gender equal representative structure.
SEZ Development in South Africa: A Case Study of Coega SEZ
Authors: Chongsheng Yang
Published: August 2024

This paper analyzes the major advantages and problems of Coega special economic zone (SEZ), the earliest and largest SEZ in South Africa, adopting the research method of a case study. The author observes and analyzes the three main participants in the development and construction of Coega SEZ, namely the government, SEZ operator (Coega Development Corporation), and SEZ enterprises, so as to clarify the attribution of the problems and provide suggestions. How the South African government at all levels understands and operates the SEZ would have a significant impact on the development of Coega, which is also the concern of investors. The multi-party system in South Africa has generated complicated partisan politics, in which different parties at all levels are formulated in the administrative system, subsequently leading to a cumbersome process of administrative procedures and policy implementation. Issues like overprotective labor laws for employees, aggressive labor unions, and frequent strikes will reduce enthusiasm from investors. In addition, deep-rooted poverty and educational plights in South Africa also reduce the competitiveness of the talent market to some extent. For the South African government and relevant authorities that are responsible for designing SEZ strategies for better development, the following issues should be their major concerns, including what the development paths of SEZs are, what roles and functions they can play at each stage of the development itself, as well as how they and the management committees can form complementary mechanisms so as to better serve zone enterprises and facilitate multiple interactions among enterprises, between enterprises and management committees, and between enterprises and government departments, eventually improving the core competitiveness and comparative advantages of Coega SEZ.
Key performance indicators and benchmarks in MCI prehospital response using technological tools: a qualitative study assessing the perception of practitioners and tool developers
Authors: Lamine Hamdi , Markou-Pappas Nikolaos , Ragazzoni Luca , Caviglia Marta
Published: August 2024

Purpose

The aim of this study is to investigate the opinions and perspectives of The Novel Integrated Toolkit for Enhanced Prehospital Life Support and Triage in Challenging and Large Emergencies (NIGHTINGALE) end-users and tool developers regarding Key Performance Indicators (KPIs) and benchmarks that assess the prehospital response to Mass Casualty Incidents (MCIs) enhanced by the NIT-MR.

Methods

A qualitative study employing focus group discussions was conducted to collect opinions and perspectives of end-users and tool developers regarding KPIs and benchmarks in MCI response using the NIT-MR. The criteria considered for the selection and distribution of participants within the groups was the nature of their involvement within the NIGHTINGALE project and their familiarity with the tools to be discussed.

Results

Thirty-one participants from different countries were included. Four themes emerged during data analysis which are: definition/explanation is the personal understanding of participants of the term KPI, process of KPI development and relationship with User Requirements is the decision process for assigning KPIs to user requirements, benchmarking is the mental process of associating a benchmark to a KPI or for developing a benchmark, and technical/medical gap is the gap of understanding between each sides’ fields.

Conclusion

This study emphasized the need for a structured approach to using KPIs and bridging the gap between technological and medical worlds, taking the NIGHTINGALE project, funded by the European Union, which aims to develop a technological toolkit for first responders in mass casualty incidents as an example. These insights are crucial for enhancing disaster response.
GRNN-based cascade ensemble model for non-destructive damage state identification: small data approach
Authors: Izonin Ivan , Kazantzi Athanasia K. , Tkachenko Roman , Mitoulis Stergios-Aristoteles
Published: August 2024

Assessing the structural integrity of ageing structures that are affected by climate-induced stressors, challenges traditional engineering methods. The reason is that structural degradation often initiates and advances without any notable warning until visible severe damage or catastrophic failures occur. An example of this, is the conventional inspection methods for prestressed concrete bridges which fail to interpret large permanent deflections because the causes—typically tendon loss—are barely visible or measurable. In many occasions, traditional inspections fail to discern these latent defects and damage, leading to the need for expensive continuous structural health monitoring towards informed assessments to enable appropriate structural interventions. This is a capability gap that has led to fatalities and extensive losses because the operators have very little time to react. This study addresses this gap by proposing a novel machine learning approach to inform a rapid non-destructive assessment of bridge damage states based on measurable structural deflections. First, a comprehensive training dataset is assembled by simulating various plausible bridge damage scenarios associated with different degrees and patterns of tendon losses, the integrity of which is vital for the health of bridge decks. Second, a novel General Regression Neural Network (GRNN)-based cascade ensemble model, tailored for predicting three interdependent output attributes using limited datasets, is developed. The proposed cascade model is optimised by utilising the differential evolution method. Modelling and validation were conducted for a real long-span bridge. The results confirm the efficacy of the proposed model in accurately identifying bridge damage states when compared to existing methods. The model developed demonstrates exceptional prediction accuracy and reliability, underscoring its practical value in non-destructive bridge damage assessment, which can facilitate effective restoration planning.
An experimental study on the applicability of acoustic emission to detection of lift-off state in gas foil bearings
Authors: Ahmadzadeh Majid , Kliemank Martin L. , Gühmann Clemens , Liebich Robert
Published: August 2024

Gas foil bearings (GFBs) are fluid dynamic bearings with applications in high-speed lightweight machinery. One of the important parameters in GFBs is the lift-off speed. It indicates a speed above which there is no occurrence of dry friction and wear between the rotor and bearing, the so-called lift-off state. There are various techniques for determination of the lift-off state. However, they come with major limitations and complexities for use in real-world applications, especially in high-speed machinery. In recent years, monitoring the lift-off condition in journal bearings based on acoustic emissions (AE) has been investigated and shown to be suitable for this type of bearing. Nevertheless, its applicability to GFBs is yet not known, as there has been no practical investigation on AE signals in GFBs. In the present work, the applicability of AE measurements to detection of lift-off state in GFBs is explored experimentally based on previous studies on journal bearings. The results demonstrate that AE measurements are a potential alternative to conventional methods in determining the lift-off state in GFBs. The comparison between features of AE signals, measured at two different locations on the bearing, with the friction torque as the reference exhibits the applicability of AE measurements to detection of lift-off state.
Implementing a Photodocumentation Program
Authors: Lai Eric K. , Slavik Evan , Ganim Bessie , Perry Laurie A. , Treuting Caitlin , Dee Troy , Osborne Melissa , Presley Cieara , Towbin Alexander J.
Published: August 2024

The widespread availability of smart devices has facilitated the use of medical photography, yet photodocumentation workflows are seldom implemented in healthcare organizations due to integration challenges with electronic health records (EHR) and standard clinical workflows. This manuscript details the implementation of a comprehensive photodocumentation workflow across all phases of care at a large healthcare organization, emphasizing efficiency and patient safety. From November 2018 to December 2023, healthcare workers at our institution uploaded nearly 32,000 photodocuments spanning 54 medical specialties. The photodocumentation process requires as few as 11 mouse clicks and keystrokes within the EHR and on smart devices. Automation played a crucial role in driving workflow efficiency and patient safety. For example, body part rules were used to automate the application of a sensitive label to photos of the face, chest, external genitalia, and buttocks. This automation was successful, with over 50% of the uploaded photodocuments being labeled as sensitive. Our implementation highlights the potential for standardizing photodocumentation workflows, thereby enhancing clinical documentation, improving patient care, and ensuring the secure handling of sensitive images.
Strategies for ammonia recovery from wastewater: a review
Authors: Farghali Mohamed , Chen Zhonghao , Osman Ahmed I. , Ali Israa M. , Hassan Dalia , Ihara Ikko , Rooney David W. , Yap Pow-Seng
Published: August 2024

The circular economy requires advanced methods to recycle waste matter such as ammonia, which can be further used as a fuel and a precursor of numerous value-added chemicals. Here, we review methods for the recovery of ammonia from wastewater with emphasis on biological and physicochemical techniques, and their applications. Biological techniques involve nitrification, denitrification, and anammox processes and the use of membrane bioreactors. Physicochemical techniques comprise adsorption, membrane filtration, ion exchange, chemical precipitation, ammonia stripping, electrochemical oxidation, photocatalytic oxidation, bioelectrochemical systems, and membrane hybrid systems. We found that nitrification and anammox processes in membrane bioreactors stand out for their cost-effectiveness, reduced sludge production, and energy efficiency. The use of struvite precipitation is an efficient, environmentally friendly, and recyclable method for ammonia removal. Membrane hybrid systems are promising for ammonia recovery, nutrient concentration, and wastewater treatment, with applications in fertilizer production and water purification. Overall, nitrogen removal ranges from 28 to 100%, and nitrogen recovery ranges from 9 to 100%.
Contrasting Linguistic Patterns in Human and LLM-Generated News Text
Authors: Muñoz-Ortiz Alberto , Gómez-Rodríguez Carlos , Vilares David
Published: August 2024

We conduct a quantitative analysis contrasting human-written English news text with comparable large language model (LLM) output from six different LLMs that cover three different families and four sizes in total. Our analysis spans several measurable linguistic dimensions, including morphological, syntactic, psychometric, and sociolinguistic aspects. The results reveal various measurable differences between human and AI-generated texts. Human texts exhibit more scattered sentence length distributions, more variety of vocabulary, a distinct use of dependency and constituent types, shorter constituents, and more optimized dependency distances. Humans tend to exhibit stronger negative emotions (such as fear and disgust) and less joy compared to text generated by LLMs, with the toxicity of these models increasing as their size grows. LLM outputs use more numbers, symbols and auxiliaries (suggesting objective language) than human texts, as well as more pronouns. The sexist bias prevalent in human text is also expressed by LLMs, and even magnified in all of them but one. Differences between LLMs and humans are larger than between LLMs.
Machine learning-based hyperspectral wavelength selection and classification of spider mite-infested cucumber leaves
Authors: Mandrapa Boris , Spohrer Klaus , Wuttke Dominik , Ruttensperger Ute , Dieckhoff Christine , Müller Joachim
Published: August 2024

Two-spotted spider mite (Tetranychus urticae) is an important greenhouse pest. In cucumbers, heavy infestations lead to the complete loss of leaf assimilation surface, resulting in plant death. Symptoms caused by spider mite feeding alter the light reflection of leaves and could therefore be optically detected. Machine learning methods have already been employed to analyze spectral information in order to differentiate between healthy and spider mite-infested leaves of crops such as tomatoes or cotton. In this study, machine learning methods were applied to cucumbers. Hyperspectral data of leaves were recorded under controlled conditions. Effective wavelengths were identified using three feature selection methods. Subsequently, three supervised machine learning algorithms were used to classify healthy and spider mite-infested leaves. All combinations of feature selection and classification methods yielded accuracy of over 80%, even when using ten or five wavelengths. These results suggest that machine learning methods are a powerful tool for image-based detection of spider mites in cucumbers. In addition, due to the limited number of wavelengths, there is also substantial potential for practical application.
Functional attributes of conifers expanding into temperate semi-arid grasslands modulate carbon and nitrogen fluxes in response to prescribed fire
Authors: Gay Justin D. , Currey Bryce , Davis Kimberley T. , Brookshire E. N. Jack
Published: August 2024

Fire exclusion is a key factor driving conifer expansion into temperate semi-arid grasslands. However, it remains unclear how reintroducing fire affects the aboveground storage of carbon (C) and nitrogen (N) in the expanding tree species and belowground in soils. To assess the impacts of fire reintroduction C and N pools and fluxes in areas of conifer expansion we targeted a region of the Northern Great Plains that has experienced extensive woody plant expansion (WPE) of two species: ponderosa pine (Pinus ponderosa) and juniper (Juniperus spp). We quantified tree mortality of both species to estimate the amount of dead biomass C and N produced by a recent prescribed fire, in addition to changes in soil C, pyrogenic C (PyC), and N concentrations across a woody-cover gradient using a before/after/control experimental design. Post-fire soil chemical analysis revealed a 2 year increase in mineral soil C, PyC and N, suggesting the return of fire led to the transfer of partially combusted plant organic matter back to the soil. Further, we found that functional trait differences between the two species influenced the distribution of living conifer biomass-N prior to fire. Despite junipers having 41% less total aboveground biomass than ponderosa, they contained two times more aboveground N. Prescribed fire resulted in 88% mortality of all mature juniper stems and increased fire severity correlated with greater pre-fire juniper cover. Ponderosa mortality varied by size class, with > 40 cm stem diameter class having only 28% mortality. High mortality and greater aboveground N storage in juniper biomass, compared to ponderosa, led to 77% of the total conifer biomass N lost. Consequently, the functional attributes of expanding trees differentially contribute to fluxes of C and N after the return of fire, with junipers acting as conduits for N movement due to their relatively higher N content in less fire-resistant tissues and ponderosa serving as important and more stable storage pools for C. Together, these findings highlight the importance of considering species-specific traits when planning WPE management strrategies at landscape-scales, particularly when goals include C storage or soil nutrient status.

Graphical abstract
Meta-analysis of Interventions for Monitoring Accuracy in Problem Solving
Authors: Janssen Noortje , Lazonder Ard W.
Published: August 2024

Accurate monitoring of performance in problem-solving tasks is an important prerequisite for students’ future academic success. A wide variety of interventions aiming to enhance students’ monitoring accuracy have been developed, but their effectiveness is not apparent from the individual studies in which they have been examined. This meta-analysis classified these interventions in terms of how they target students’ monitoring and investigated their relative effectiveness to improve monitoring accuracy in problem-solving tasks. Findings across the 35 included studies indicated that all interventions combined have a small positive effect on students’ monitoring accuracy (g = 0.25). Intervention type moderated the findings. Interventions on the whole task, metacognitive knowledge, and external standards improved monitoring accuracy. On the other hand, interventions targeting the timing of metacognitive judgment negatively impacted monitoring accuracy and significantly differed from all other interventions. Exploratory moderator analyses of study features indicated that secondary school students benefited least from the interventions compared to primary school students and adults, laboratory studies showed larger effects than classroom studies, and interventions were more effective for retrospective confidence judgments than for judgments of learning. For educational practice, interventions targeting the whole task, metacognitive knowledge, and external standards are recommended, while reconsideration and possibly discontinuation of timing interventions is needed.
Challenges in Promoting Self-Regulated Learning in Technology Supported Learning Environments: An Umbrella Review of Systematic Reviews and Meta-Analyses
Authors: Prasse Doreen , Webb Mary , Deschênes Michelle , Parent Séverine , Aeschlimann Franziska , Goda Yoshiko , Yamada Masanori , Raynault Audrey
Published: August 2024

Supporting learners’ self-regulated learning (SRL) processes and skills is crucial for effective learning, especially in online learning environments. In recent years, research on SRL and how it can be supported by technology has proliferated, resulting in many systematic reviews. The aims of this umbrella review are to provide orientation in a growing field, to identify challenges in the design of computer-assisted SRL (CA-SRL) supports and to derive future research needs. We identified and analysed 31 systematic reviews and meta-analyses that investigated SRL supports in computer-based, online and blended learning environments. The synthesis of the reviews highlights the critical importance of adopting comprehensive approaches in designing and implementing CA-SRL supports which integrate a variety of direct and indirect CA-SRL supports across the entire SRL cycle. The findings also call for greater precision in defining and categorising CA-SRL supports and their theoretical foundations to enhance comparability of research in this area. Finally, we conclude by providing recommendations for future research and development to effectively promote SRL for learners.
Neutron Activation Analysis Reveals Jamaican Origin of Afro-Caribbean Ware Excavated from the Cayman Islands
Authors: Petras Elysia M. , MacDonald Brandi L.
Published: August 2024

Afro-Caribbean ware is Caribbean-made pottery manufactured both at the craft and industrial scale by enslaved and free potters of African descent. Previous sourcing studies have shown historic variation in centers of production and market distribution of these wares across the Caribbean. We used Neutron Activation Analysis (NAA) on a clay sample and 13 low-fired coarse earthenware sherds excavated from the historic-period Jackson Wall Manor site on Grand Cayman. We found that the Grand Cayman clay was compositionally inconsistent with any previously analysed ceramic sherds in the University of Missouri Research Reactor (MURR) NAA Caribbean database, and that the ceramic samples excavated on Grand Cayman showed high statistical correlation with Jamaican ceramic groups. These findings suggest that coarse earthenware on Grand Cayman was transported from Jamaica, a nearby colony with established potteries and markets, rather than being produced locally. Jamaican yabbas, which combined African and European manufacturing technique and forms, were imported into Grand Cayman to fit local needs.
Understanding Artificial Intelligence Diffusion through an AI Capability Maturity Model
Authors: Hansen Hans Fredrik , Lillesund Elise , Mikalef Patrick , Altwaijry Νajwa
Published: August 2024

The recent advancements in the field of Artificial Intelligence (AI) have sparked a renewed interest in how organizations can potentially leverage and gain value from these technologies. Despite the considerable hype around AI, recent reports indicate that a very small number of organizations have managed to successfully implement these technologies in their operations. While many early studies and consultancy-based reports point to factors that enable adoption, there is a growing understanding that adoption of AI is rather more of a process of maturity. Building on this more nuanced approach of adoption, this study focuses on the diffusion of AI through a maturity lens. To explore this process, we conducted a two-phased qualitative case study to explore how organizations diffuse AI in their operations. During the first phase, we conducted interviews with AI experts to gain insight into the process of diffusion as well as some of the key challenges faced by organizations. During the second phase, we collected data from three organizations that were at different stages of AI diffusion. Based on the synthesis of the results and a cross-case analysis, we developed a capability maturity model for AI diffusion (AICMM), which was then validated and tested. The results highlight that AI diffusion introduces some common challenges along the path of diffusion as well as some ways to mitigate them. From a research perspective, our results show that there are some core tasks associated with early AI diffusion that gradually evolve as the maturity of projects grows. For professionals, we present tools for identifying the current state of maturity and providing some practical guidelines on how to further implement AI technologies in their operations to generate business value.
Determinants of artificial intelligence adoption: research themes and future directions
Authors: Khanfar Ahmad A. , Kiani Mavi Reza , Iranmanesh Mohammad , Gengatharen Denise
Published: August 2024

The adoption of artificial intelligence (AI) systems is on the rise owing to their many benefits. This study conducted a bibliometric analysis to identify (1) how the literature on AI adoption has evolved over the past few years, (2) key themes associated with AI adoption in the literature, and (3) the gaps in the literature. To achieve these objectives, we utilised the Biblioshiny of R-package bibliometric analysis tool to analyse the AI adoption literature. A total of 91 articles were reviewed and analysed in this study. Four major themes were identified: AI, machine learning, the unified theory of acceptance and use of technology (UTAUT) model and the technology acceptance model (TAM). Using a content analysis of the identified themes, the study gained additional insight into the studies on AI adoption. Previous studies have been limited to specific industries and systems, and adoption theories like the UTAUT and TAM have also been utilised to a limited extent. Directions for future studies were provided.
A second homotopy group for digital images
Authors: Lupton Gregory , Musin Oleg , Scoville Nicholas A. , Staecker P. Christopher , Treviño-Marroquín Jonathan
Published: August 2024

We define a second (higher) homotopy group for digital images. Namely, we construct a functor from digital images to abelian groups, which closely resembles the ordinary second homotopy group from algebraic topology. We illustrate that our approach can be effective by computing this (digital) second homotopy group for a digital 2-sphere.
Accuracy of Mothers’ Perception of Birth Size to Predict Birth Weight Data in Bangladesh
Authors: Khan Jahidur Rahman , Bakar K. Shuvo , Awan Nabil , Muurlink Olav , Homaira Nusrat
Published: August 2024

Objectives

The prevalence of low birth weight (LBW) is an important indicator of child health and wellbeing. However, in many countries, decisions regarding care and treatment are often based on mothers’ perceptions of their children’s birth size due to a lack of objective birth weight data. Additionally, birth weight data that is self-reported or recorded often encounters the issue of heaping. This study assesses the concordance between the perceived birth size and the reported or recorded birth weight. We also investigate how the presence of heaped birth weight data affects this concordance, as well as the relationship between concordance and various sociodemographic factors.

Methods

We examined 4,641 birth records reported in the 2019 Bangladesh Multiple Indicator Cluster Survey. The sensitivity-specificity analysis was performed to assess perceived birth size’s ability to predict LBW, while Cohen’s Kappa statistic assessed reliability. We used the kernel smoothing technique to correct heaping of birth weight data, as well as a multivariable multinomial logistic model to assess factors associated with concordance.

Results

Maternally-perceived birth size exhibited a low sensitivity (63.5%) and positive predictive value (52.6%) for predicting LBW, but a high specificity (90.1%) and negative predictive value (93.4%). There was 86.1% agreement between birth size and birth weight-based classifications (Kappa = 0.49, indicating moderate agreement). Smoothed birth weight data did not improve agreement (83.4%, Kappa = 0.45). Of the sociodemographic factors, early marriage was positively associated with discordance (i.e., overestimation).

Conclusions

An important consideration when calculating the LBW prevalence is that maternally perceived birth size is not an optimal proxy for birth weight. Focus should be placed on encouraging institutional births and educating community health workers and young mothers about the significance of measuring and recording birth weight.
Robust Optimization Using the Mean Model with Bias Correction
Authors: Oliver Dean S.
Published: August 2024

Optimization of the expected outcome for subsurface reservoir management when the properties of the subsurface model are uncertain can be costly, especially when the outcomes are predicted using a numerical reservoir flow simulator. The high cost is a consequence of the approximation of the expected outcome by the average of the outcomes from an ensemble of reservoir models, each of which may need to be numerically simulated. Instead of computing the sample average approximation of the objective function, some practitioners have computed the objective function evaluated on the “mean model,” that is, the model whose properties are the means of properties of an ensemble of model realizations. Straightforward use of the mean model without correction for bias is completely justified only when the objective function is a linear function of the uncertain properties. In this paper, we show that by choosing an appropriate transformation of the variables before computing the mean, the mean model can sometimes be used for optimization without bias correction. However, because choosing the appropriate transformation may be difficult, we develop a hierarchical bias correction method that is highly efficient for robust optimization. The bias correction method is coupled with an efficient derivative-free optimization algorithm to reduce the number of function evaluations required for optimization. The new approach is demonstrated on two numerical porous flow optimization problems. In the two-dimensional well location problem with 100 ensemble members, a good approximation of the optimal location is obtained in 10 function evaluations, and a slightly better (nearly optimal) solution using bias correction is obtained using 216 function evaluations.
Motivating and demotivating teaching styles: A comparison among planned, adopted, and perceived
Authors: Wang Jiawei , Meng Weiqing , Xing Qiang , Moè Angelica
Published: August 2024

Grounded in Self-Determination Theory (SDT), this study aimed at comparing autonomy-supportive (e.g., the teacher allows students to choose a project they are interested in from several options), structuring (e.g., the teacher breaks down problem-solving steps into manageable parts to help students understand), controlling (e.g., the teacher strictly enforces classroom rules and punishes non-compliance), and chaotic (e.g., despite some students being disruptive in class, the teacher does not intervene) planned, adopted, and student-perceived (de)motivating teaching styles. A mixed method was adopted by involving 20 secondary school teachers and their 38 students in focus group interviews and in filling in a measure of (de)motivating teaching styles. While the questionnaire data did not reveal significant differences, the focus group interviews uncovered noteworthy distinctions. The data from focus group interviews with teachers and students revealed that the proportion of teachers adopting a controlling teaching style is higher than those who had initially planned to use this style. Simultaneously, the proportion of teachers adopting a controlling style is lower than the proportion of students perceiving this style. Thematic analysis of data gathered from focus group interviews with teachers identified five main themes influencing teachers’ adoption of teaching styles: “teacher factors”, “school factors”, “student factors”, “management and relationships”, and “teaching methods and design”. Overall, this study provides a more comprehensive understanding of (de)motivating teaching styles in China. Educational implications are discussed.
Steepest Geometric Descent for Regularized Quasiconvex Functions
Authors: Daniilidis Aris , Salas David
Published: August 2024

We establish existence of steepest descent curves emanating from almost every point of a regular locally Lipschitz quasiconvex functions, where regularity means that the sweeping process flow induced by the sublevel sets is reversible. We then use max-convolution to regularize general quasiconvex functions and obtain a result of the same nature in a more general setting.
Competition Between Growth and Removal in Zirconia Nanocrystal-Derived Tribofilms: The Role of Co-additives
Authors: LaMascus Parker , Elinski Meagan B. , Delghandi Daniel , Nautiyal Pranjal , Griffin Julia , Zheng Lei , Jackson Andrew , Wiacek Robert J. , Carpick Robert W.
Published: August 2024

Antiwear additives permit energy-efficient lubrication of gearboxes, bearings, and other tribological interfaces. We study zirconia (ZrO2) nanocrystal additives, which readily form protective tribofilms in tribological contacts. Our prior work demonstrated cooperative antiwear performance between ZrO2 and the S- and P-based co-additives in fully formulated hydrocarbon gear oils. Here, we extend that work by examining the growth kinetics of the ZrO2 tribofilms, including the influence of the co-additives. In the boundary lubrication regime for mixed rolling-sliding contacts, the initial phase of ZrO2 tribofilm growth is soon overtaken by removal processes, phenomena whose importance has gone unnoticed in prior work. Tribofilm removal affects the steady-state thickness and morphology of the tribofilm as well as its growth kinetics. The S- and P-based co-additives are incorporated into the ZrO2 tribofilm, and alter the competition between the growth and removal processes, increasing initial net growth rates per contact cycle and contributing to a more polished final interface. This work highlights the significance of removal processes in determining tribofilm antiwear performance, and suggests several routes for improving tribofilm growth kinetics using co-additives.

Graphical abstract
Isolation of new indole alkaloid triglucoside from the aqueous extract of Uncaria rhynchophylla
Authors: Koseki Yuta , Nishimura Hiroaki , Asano Ryuji , Aoki Katsuyuki , Shiyu Li , Sugiyama Ryosuke , Yamazaki Mami
Published: August 2024

Uncaria rhynchophylla (Miq.) Miq. (Rubiaceae) is widely used as a botanical raw material for traditional Japanese and Chinese medicines. However, not all of its potentially bioactive constituents have been isolated and characterized. Herein, one new indole alkaloid triglucoside (1), nine known alkaloids (2–10) and thirteen known non-alkaloids (11–23) were isolated from the aqueous extract of Uncaria rhynchophylla hook and structurally characterized 1H and 13C NMR and high-resolution electrospray ionization mass spectrometry. The absolute configurations of isolated compounds (1, 2 and 3) were determined by the X-ray diffraction analysis of their single crystals obtained using a micro-drop crystallization technique. This technique allows single crystals to be obtained from samples as small as 50 µg, thus providing detailed structural information even on minor constituents and enabling the accurate quality monitoring of botanical raw materials more accurately.

Graphical abstract
Boolean operators and neural networks
Authors: Marziali Sara
Published: August 2024

We compute the homogeneous ideals of varieties, in a projective space of tensors, associated to different choices of the Boolean operators that describe the decision process in small neural networks. We prove that, starting with networks with three nodes, the varieties associated to different Boolean operators are all distinct.
Normative Challenges of Risk Regulation of Artificial Intelligence
Authors: Orwat Carsten , Bareis Jascha , Folberth Anja , Jahnel Jutta , Wadephul Christian
Published: August 2024

Approaches aimed at regulating artificial intelligence (AI) include a particular form of risk regulation, i.e. a risk-based approach. The most prominent example is the European Union’s Artificial Intelligence Act (AI Act). This article addresses the challenges for adequate risk regulation that arise primarily from the specific type of risks involved, i.e. risks to the protection of fundamental rights and fundamental societal values. This is mainly due to the normative ambiguity of such rights and societal values when attempts are made to select, interpret, specify or operationalise them for the purposes of risk assessments and risk mitigation. This is exemplified by (1) human dignity, (2) informational self-determination, data protection and privacy, (3) anti-discrimination, fairness and justice, and (4) the common good. Normative ambiguities require normative choices, which are assigned to different actors under the regime of the AI Act. Particularly critical normative choices include selecting normative concepts by which to operationalise and specify risks, aggregating and quantifying risks (including the use of metrics), balancing value conflicts, setting levels of acceptable risks, and standardisation. To ensure that these normative choices do not lack democratic legitimacy and to avoid legal uncertainty, further political processes and scientific debates are suggested.
Personalentwicklung als Profession? Zur vermittelnden Funktion von Personalentwicklung in organisationalen Widersprüchen
Authors: Weisenburger Nathalie
Published: August 2024

Dieser Beitrag in der Zeitschrift „Gruppe. Interaktion. Organisation. (GIO)“ stellt die Ergebnisse einer Studie zur Rolle und Funktion der Personalentwicklung (PE) im Spannungsfeld zwischen Organisation, Person und Profession vor. Es werden die subjektiven Perspektiven der Praktiker/-innen in den Fokus gerückt und ihre Selbstverständnisse und Handlungsorientierungen vorgestellt. Es zeigt sich, dass sich diese zwischen gegensätzlichen Positionen in Unternehmen bewegen. Diskutiert werden das Kernverständnis der Tätigkeit als Personalentwickler/-in vor dem Hintergrund steigender Anforderungen sowie der Umgang mit Spannungsfeldern durch die PE-Praktiker und der Mehrwert, den eine an Professionen ausgerichtete PE mit sich bringen kann.
“We are protectors, not protestors”: global impacts of extractivism on human–nature bonds
Authors: Hanaček Ksenija , Tran Dalena , Landau Arielle , Sanz Teresa , Thiri May Aye , Navas Grettel , Del Bene Daniela , Liu Juan , Walter Mariana , Lopez Aida , Roy Brototi , Fanari Eleonora , Martinez-Alier Joan
Published: August 2024

This article analyzes the global impacts of extractivism on human–nature bonds. To do so, we rely on socio-ecological conflict data from the Global Atlas of Environmental Justice. Over 1800 cases involving resistance to the destruction of nature, cultures, cosmologies, worldviews, ancestral origins, and sacred places are analyzed using log-linear regression compared to 1600 cases that do not report such loss. The impact is especially visible when mineral ores, plantation products, and crude oil are extracted. The results indicate that affected groups are Indigenous peoples, farmers, peasants, pastoralists, and religious groups. In conflict outcomes, 79% of cases with refusal of compensation indicate impacts on human–nature bonds. Furthermore, in those cases where assassinations of activists occurred, 68% have observed impacts on human–nature bonds. Protecting human–nature bonds is a critical component for achieving social, economic, and environmental sustainability and justice against extractivism embedded in colonial relations playing against such bonds and environmental protectors.
Emotional attachment and philosophical worldviews explain human connectedness to nature in abandoned rural Spain
Authors: López-Zayas C. , Castro A. J. , Requena-Mullor J. M. , López-Rodríguez M. D. , Garau E. , Quintas-Soriano C.
Published: August 2024

Land abandonment and rural depopulation are escalating worldwide, presenting sustainability dilemmas for both rural and urban regions. However, there remains a dearth of research on the sociocultural dimensions of abandonment from a local standpoint. This investigation focuses on a case study conducted in southeastern Spain, wherein a social survey was used to evaluate the perspectives of local communities concerning human–nature interconnectedness, land abandonment, and their impacts on quality of life. A survey campaign was administered in the case study region during the spring of 2021, and 122 surveys were collected. The findings identify, in the context of the progressive abandonment of rural lands in Spain, key factors that explain the desire of local people to inhabit and not abandon rural regions in southeastern Spain. Our results also show a strong connection between people and nature in rural Spain, which is explained by the capacity of locals to form relational values in rural environments and the existence of philosophical worldviews and emotional attachments to rural lifestyles. However, barriers to not abandoning rural environments were also identified, including a lack of professional and economic opportunities. Our results suggest that the mitigation of depopulation in rural areas in Spain requires actions to foster land stewardship and address socioeconomic imbalances.
Backside Analysis Strategy to Identify a Package-Related Failure Mode at an Automotive Magnetic Sensor Device
Authors: Simon-Najasek M. , Naumann F. , Huebner S. , Lejoyeux M. , Altmann F. , Lindner A.
Published: August 2024

This paper presents a root cause analysis case study of defective Hall effect sensor devices. The study identified a complex failure mode caused by chip–package interaction, which has a similar signature to discharging defects such as ESDFOS (electrostatic discharge from outside to surface). However, the study revealed that the defect was induced by local mechanical force applied to IC structures due to the presence of large irregular shaped filler particles within the mold compound. Extensive failure analysis work was conducted to identify the failure mode, including the development of a new backside analysis strategy to preserve the mold compound during IC defect localization and screening. A combination of different failure analysis techniques was used, including CMP delayering, PFIB trenching, SEM PVC imaging and large area FIB cross-sectioning. The study found that the mold compound of the package caused thermo-mechanical strain onto the silica filler particle due to epoxy shrinkage during the molding process. Additionally, extra-large, irregularly shaped filler particles (called twin particles), located on top of the chip surface, can cause locally high compression stresses onto the IC layers, initiating cracks in the isolation layers under certain conditions forming a leakage path over the time. Thermo-mechanical finite element analysis was applied to verify the mechanical load condition for these large irregular shaped filler particles. As a result, an additional polyimide layer was introduced onto the IC to mitigate the mechanical stress of mold compound particles to avoid this failure mode.