bluuebunny/crossref_metadata_2025 huggingface dataset:
A disrupted learning mechanism in standard quantum systems followed by their self-organizing process
Authors: Shushi Tomer
Published: October 2024

Recently, the fusion between quantum mechanics and machine learning has gained much attention, where classical machine learning algorithms are adapted for quantum computers to significantly amplify data analysis by leveraging the unique effects of quantum reality. In this short paper, by focusing on the quantum trajectories of particles, we find that under general requirements, quantum systems follow a disrupted version of the gradient descent model, a basic machine learning algorithm, where the learning is distorted due to the self-organizing process of the quantum system. Such a learning process is possible only when we assume dissipation, i.e., that the quantum system is open. The friction parameter determines the nonlinearity of the quantum system. We then provide an empirical demonstration of the proposed model.
Navigating Federal and State Laws Regarding the Prescription of Opioids
Authors: Kass Joseph S. , Rose Rachel V.
Published: October 2024

Since 2000, the opioid epidemic has claimed the lives of more than 500,000 people and policies regarding the prescription of opioids for chronic pain have undergone drastic changes. While neurologists account for a small number of overall opioid prescriptions, they may treat patients on opioids, prescribed by other physicians or obtained illicitly, and need to be aware of the latest practice guidelines and the legal regime regulating opioid prescriptions.
Principles of Pain Management
Authors: Hogans Beth B.
Published: October 2024

Objective

This article introduces the general principles of assessing, diagnosing, and managing pain relevant to neurologic practice.

Latest Developments

Scientific understanding of and clinical practices related to pain and pain management are advancing. The field is remarkable for the diversity of health professions engaged in this effort, including physicians, scientists, psychologists, pharmacists, and many others. Pain classification is transforming with pending changes to the International Classification of Diseases diagnostic coding system, and pain assessment has moved toward consistent application of the biopsychosocial model. The diagnosis of pain has continued to become more sophisticated with the development of additional testing modalities, clearer classification systems, and diagnostic criteria. Pain management requires both pharmacologic and nonpharmacologic elements; systematic review evidence for both of these and interventional and surgical management are increasingly available. The context of treatment remains important given the impact of social determinants of health and limitations of access to diagnostic and treatment resources. Due to global and interprofessional collaborations as well as new research funding, the outlook is positive.

Essential Points

Pain is a protean experience for humans; functional MRI (fMRI) and other research modalities show that pain perception is highly multifocal, and modulation occurs at many nervous system levels. Neurologists bring special skills to pain evaluation and management, are well equipped to appreciate both the focal and diffuse nature of pain, and can envision how pain attenuates sleep, cognitive function, mobility, motivation, and social connection. By operationalizing expert knowledge of the nervous system, implementing relevant therapies, and collaborating with diverse health professions to manage pain, neurologists can succeed at and find meaning in optimizing patient outcomes.
Pediatric Pain
Authors: Lebel Alyssa , Schuster Nathaniel M.
Published: October 2024

OBJECTIVE

This article reviews pain disorders encountered in pediatric neurology practice and provides current information regarding the assessment and treatment of pediatric chronic pain.

LATEST DEVELOPMENTS

Data about pediatric pain management remain sparse, owing to a dearth of controlled trials and longitudinal studies in these patients. However, the field of pain management and understanding of central and peripheral pain processing has expanded to allow more effective treatment of a broad group of children and adolescents with pain associated with neurologic disease. Neuroimaging visualizes sensory and nonsensory systems, and genetic markers of sensitivity and disease may guide specific therapy. The concept of central sensitization in chronic pain disorders has supported the development of multidisciplinary paradigms for the comprehensive care of these patients.

ESSENTIAL POINTS

Pain involves sensory activation and central nervous system modulation in pediatric patients. Pediatric neurologists should be prepared to define, investigate, and treat pain disorders in this complex patient population. Appropriate interventions during childhood may attenuate or prevent chronic pain later in life. Current interventions include behavioral, physical, and pharmacologic approaches, as well as potential noninvasive tools for neuromodulation. Research is progressing in sensory measurement, neuroimaging, genetics, and neuroinflammation to guide future targeted therapies.
CENP-C-targeted PLK-1 regulates kinetochore function in C. elegans embryos
Authors: Bel Borja Laura , Taylor Samuel J. P. , Soubigou Flavie , Pelisch Federico
Published: October 2024

Polo-like kinase 1 (PLK-1) is present in centrosomes, the nuclear envelope and kinetochores and plays a significant role in meiosis and mitosis. PLK-1 depletion or inhibition has severe consequences for spindle assembly, spindle assembly checkpoint (SAC) activation, chromosome segregation and cytokinesis. BUB-1 targets PLK-1 to the outer kinetochore and, in mammals, the inner kinetochore PLK1 targeting is mediated by the constitutive centromere associated network (CCAN). BUB-1-targeted PLK-1 plays a key role in SAC activation and has a SAC-independent role through targeting CDC-20. In contrast, whether there is a specific, non-redundant role for inner kinetochore targeted PLK-1 is unknown. Here, we used the Caenorhabditis elegans embryo to study the role of inner kinetochore PLK-1. We found that CENP-C, the sole CCAN component in C. elegans and other species, targets PLK-1 to the inner kinetochore during prometaphase and metaphase. Disruption of the CENP-C–PLK-1 interaction leads to an imbalance in kinetochore components and a defect in chromosome congression, without affecting CDC-20 recruitment. These findings indicate that PLK-1 kinetochore recruitment by CENP-C has at least partially distinct functions from outer kinetochore PLK-1, providing a platform for a better understanding of the different roles played by PLK-1 during mitosis.
Practical Tips for Starting a Student-Run Free Eye Clinic
Authors: Porter Robert , Leone Adam , Reinisch Cameron , Murphy Alec , Linne Courtney , Regenold Jonathan , Kim Hyun Jun , Kelly Lisa
Published: October 2024

Student-run free clinics serve three primary functions: 1) providing basic medical services for the uninsured and underserved in our communities, 2) supporting the training of medical providers, and 3) advocating for medically underserved communities. Despite the multiple benefits that student-run free clinics can provide, the process of founding a clinic is a significant challenge, even for highly motivated students. Here, we present 12 tips generated by students and residents at the University of Cincinnati College of Medicine based on their combined experience in founding the Bearcat Eye Service (BES), a clinic that provides basic ophthalmic screenings. These tips were developed to provide a framework for those interested in founding a student-run free clinic or expanding ophthalmic care in their communities.
Monitoring the Readiness of Future Economists to Use Artificial Intelligence in the Banking Sector
Authors: Burmistrova N. , Kornilceva E. , Lebed' M. , Shurygin K.
Published: October 2024

In the context of the digital transformation of modern society, the study of the problem of introducing artificial intelligence into all spheres of life, including the sphere of economics and finance, is extremely relevant. The purpose of this article is an attempt to analyze the readiness of future economists in the school-university system to use artificial intelligence in the context of developing digital financial literacy. The authors studied the nature of the influence of artificial intelligence on the formation of basic competencies necessary in the era of digitalization of economic education, through the prism of the views of the younger generation. The importance of various aspects of the digital transformation of society, which are in the focus of attention of global cooperation organizations (UNESCO, World Bank, etc.) in the interests of sustainable development, is noted. Using Google-Forms tools, a sociological survey was conducted among students of the Financial University under the Government of the Russian Federation (Omsk branch) and students of specialized economic classes at Gymnasium 19 in the city of Omsk on the topic “The attitude of future economists to the use of artificial intelligence in the banking sector.” The results of the analysis of the obtained empirical data made it possible to state the complex and ambiguous nature of the influence of artificial intelligence on the young generation of future economists in the conditions of total digitalization. Along with the positive attitude of young people towards the prospects for the introduction of artificial intelligence, the risks of a decrease in natural intelligence against the backdrop of digitalization reaching all spheres of life have been identified. This, in turn, requires the formation of value guidelines and the development of a strategy for the continuous development of future economists in the digital society in the context of the active implementation of artificial intelligence.
Electronic Textbook in Higher Mathematics Based on Visualization of Educational Content
Authors: Konnova Larisa , Stepanyan I.
Published: October 2024

The strategy for the digital transformation of the science and higher education industries sets one of the tasks to create digital educational services that allow the implementation of individual learning trajectories. According to this goal, the main content component of the educational process – the textbook – should also change.

Since the transition of educational literature to electronic form, the pedagogical community has been developing theoretical foundations and technologies for designing electronic textbooks in new formats. The use of digital tools makes it possible to create different types of textbooks in the same discipline, differing in purpose, depth and target audience. This approach promotes individualization of learning.

The article presents the format of electronic educational literature, based on visualization of educational content and dosing of information. The authors embodied this idea in mathematics textbooks for first-year undergraduate students “Linear Algebra EASILY!” and “Mathematical analysis EASILY!”. The experience of introducing them into the educational process has shown that they are in demand by students for self-study, and, to a greater extent, by students who experience difficulties in mastering higher mathematics. The described format can be used to create electronic textbooks in various disciplines and will be useful for distance learning students, foreign students and students with disabilities.
Methodology for managing the quality of education based on integrative assessment
Authors: Zakieva Rafina
Published: October 2024

The article focuses on the study of the theoretical and methodological foundations of education quality management at a technical university, based on fundamental research and key ideas of scientists; theories of vocational, engineering and technical education; conceptual provisions, principles of assessment activities, approaches and research methods; the conceptual-categorical apparatus is clarified.

Aim. To identify and generalize the theoretical and methodological foundations of education quality management at a technical university, to find its niche, basis and «foundation».

Methods. Analysis of philosophical, sociological, psychological and pedagogical literature, scientific sources; state and regulatory documents on the research problem; analysis of the main concepts of this work.

Results. The scientific foundations for creating an education quality management system at a technical university have been developed based on integrative assessment and monitoring of student professional development using digital resources, which ensures continuous correlation of this information with the requirements for a graduate specified in the Federal State Educational Standard and the OPOP (for a specific training profile), and adjustment taking into account these indicators of didactic conditions for the professional and personal development of students.

Scientific novelty. Based on a generalization of the experience of fundamental research and key ideas of scientists in the field of pedagogy, sociology, psychology, philosophy a conceptual position is formulated on which the mechanism for managing the quality of education at a technical university is based.

The practical significance of the research results is determined by the fact that in the practice of managing the quality of education, it becomes possible to evaluate the professional development of students on an integrative basis, predict changes in the development of students, and plan specific management decisions within the framework of this system.
Impact of GLP-1 Agonists on Depression Treatment: A Literature Review
Authors: Lemieszek Paulina , Rudnicka Katarzyna , Sajkiewicz Ilona , Miga-Orczykowska Nadia , Jasiuk Ilona , Wójtowicz Justyna , Pustelniak Martyna , Krukar Katarzyna , Łukaszewska Ewa , Kister Klaudia , Chrościński Kamil , Laskowski Jakub
Published: October 2024

Introduction
Depression is increasingly recognized as a major global health issue, driven by neurobiological, genetic, and environmental factors. Despite extensive research, understanding depression remains challenging due to its complexity and the lack of biomarkers. Recent studies highlight a link between depression and metabolic disturbances, emphasizing the need for alternative therapeutic approaches.
Purpose
This review aims to explore the therapeutic potential of GLP-1 (glucagon-like peptide-1) in treating depression, focusing on its impact on neurogenesis, neuroinflammation, neurotransmitter imbalances, and synaptic dysfunction.
Materials and Methods
A systematic review was conducted by analyzing literature from databases such as PubMed and Google Scholar, covering studies from 2003 to 2024. The review focused on keywords related to GLP-1, depression, and diabetes.
Description of the State of Knowledge
This section discusses the neurobiological mechanisms of depression, including neuroinflammation, neurotransmitter imbalances, and impaired neurogenesis. It highlights the potential of GLP-1 agonists to address these issues and improve mood and cognitive function.
Conclusion
The review concludes that GLP-1 holds promise as a therapeutic target for depression. Beyond its metabolic roles, GLP-1 can influence brain regions involved in mood regulation, enhance neurogenesis, reduce neuroinflammation, and improve neurotransmitter balance. These effects suggest that GLP-1-based therapies could offer new treatment options for depression, potentially improving outcomes beyond traditional antidepressants.
A Review of Cradle-to-Gate Greenhouse Gas Emission Factors for Canada’s Harvested Wood Products
Authors: Desjardins Sabrina M. , Chen Jiaxin , Ter-Mikaelian Michael T.
Published: October 2024

With the previous decade’s (2010 through 2019) greenhouse gas emissions remaining the highest on record, focus on emissions mitigation efforts is paramount. Harvested wood products (HWPs) can store carbon for various timespans depending on the product and its end uses. Life cycle inventories (LCIs) are the base for life cycle analyses (LCAs), as they represent a comprehensive catalogue of the raw data essential to complete an LCA. However, most LCI documentation is in the form of case studies of different types of HWPs, with varying LCI results that reflect varied system boundaries, case-specific conditions, and assumptions. Our goal was to conduct a systematic literature review to evaluate, analyze, and synthesize previously reported Canadian HWP data and to initiate a Canadian database based on reported cradle-to-gate HWP emission factors. HWPs were categorized as lumber, traditional structural panels, mass timber, nonstructural panels, and wood pellets. Based on our analysis, we found that softwood lumber produced the lowest cradle-to-gate emission factor (61.99 kg of CO2 equivalent [CO2eq] per m3 HWP) while I-joists produced the highest (218.55 kg of CO2eq per m3 HWP). Resource extraction emissions accounted for most of the overall emissions for softwood lumber, oriented strand board, cross-laminated timber, and glue-laminated timber. Meanwhile, manufacturing accounted for most of the emissions for plywood, I-joists, cellulosic fiberboard, particleboard, and wood pellets. Substantial gaps exist in published LCI data and, when possible, publishing detailed LCI data is encouraged to support additional HWP life cycle analyses.
The Many Dimensions of Academic Ableism: Career and Technical Education (CTE) Faculty Attitudes in Engaging with Disabled Community College Students
Authors: Nachman Brett
Published: October 2024

Career and technical education (CTE) faculty play significant roles in supporting their students down viable professional pathways. Yet existent work has not explored their attitudes of or engagement with disabled learners, who remain greatly unemployed. This hermeneutic phenomenological study draws on 20 interviews to uncover community college CTE faculty attitudes that shape their engagement with disabled learners. Findings illuminate how frustration, uncertainty, admiration, and confidence manifest and influence academic ableism. Implications prompt colleges to make sweeping and systematic changes in providing consistent programming (e.g., lunch-and-learn events) and shifting mindsets around disability (e.g., anti-ableism trainings, naming disability as diversity in institutional policies).
Metallic Mode: Exploring African Speculative Fiction through the Affordances of Metal
Authors: Woods Joanna
Published: October 2024

ABSTRACT: African sf occupies a particularly interesting interstitial space, blurring lines between science fiction and the fantastical. The literature defies easy categorization. This paper looks at the associations between metal and Africa to explore such defiance and to develop the idea that African sf can be called a "metallic mode." I explore the affordances of metal in two contemporary texts: Namwali Serpell's The Old Drift (2019) and Andrew Miller's Dub Steps (2015). Informed by Caroline Levine's work on form and its affordances , I examine the potential we might find in the properties of metal to think and speak about African sf. The paper ultimately looks at how the literature communicates through metallic historicity, malleability, ductility, non-linearity, recyclability, conductivity, and technological capability to cast African sf as a complex mode that forges a space of its own in the broader terrain of sf.
Authoritarianism and Free Markets: Notes on Fascism, Populism, and Economics
Authors: Finchelstein Federico
Published: October 2024

ABSTRACT: Is there a link between authoritarian politics and free market economics? How important has economic theory been historically to the rise of authoritarian systems and ideologies? Are fascism and populism determined by economic priorities or economic interests? In this article, I argue that economics was not that important, and certainly not as important as politics was, for fascists and populists. I then address how this is changing in the present cases of wannabe fascist populists such as Donald Trump in the United States and Javier Milei in Argentina.
Infrared emissivity measurement methods considering target reflective characteristics
Authors: Liu Yin , Li Yiwen , Ma Simin , Zhang Puyousen , Li Yao , Fan Xiumei , Li Weiqin
Published: October 2024

Emissivity measurements are of great significance for infrared thermal radiation and
infrared remote sensing. However, traditional methods often face
challenges such as difficulties in non-contact measurement, small
measurement areas, and unsuitability for non-Lambertian surfaces. To
address these issues, we propose the reflective distribution model
integral method (RDMIM). This method is based on a reflective
distribution model using the scattering-reflective deviation angle
(SRDA). By regressing and integrating the object’s reflective
distribution model, it achieves accurate non-contact measurement of
non-Lambertian surfaces under normal temperature conditions.
Additionally, the measurement scheme has been further optimized to
improve measurement efficiency while ensuring the accuracy of the
model regression. Finally, the proposed RDMIM method has been
validated through experimental measurements. The results have shown
that this method has advantages in non-contact and large-area
measurements. Moreover, the systematic error is smaller when the
reflective characteristics of the reference body and the target are
relatively similar.
Coherent passive optical network: applications, technologies, and specification development [Invited Tutorial]
Authors: Jia Zhensheng , Zhang Haipeng , Choutagunta Karthik , Campos L. Alberto
Published: October 2024

This paper presents a comprehensive overview of the emerging coherent passive optical network (CPON) technology and its role in the evolution of next-generation PON architectures. After reviewing the fundamental principles of traditional time-division multiplexed PON and tracking its development across successive standards, the unique benefits of applying coherent detection to PONs are examined. These include enhanced reach, increased split ratios, and improved overall network scalability. The paper explores various use cases, deployment scenarios, and architectural options for CPONs. Critical enabling technologies driving CPON development are analyzed, including upstream preamble design and burst-mode detection, techniques for transceiver cost reduction and implementation simplification, forward error correction, and out-of-band communication channels. Finally, the major industry standardization efforts currently underway to specify CPON across the physical, media access control, and system architecture layers are reviewed. By cohesively covering CPON’s evolution from core concepts to real-world specifications, this tutorial paper provides a definitive reference on this disruptive access network technology.
Modeling refractive error populations by Weibull distribution for the minimum visual correction diopter range in XR systems
Authors: Ou Chung-Jen
Published: October 2024

The determination of the minimum diopter correction requirements for XR systems is a critical task that necessitates a rigorous, evidence-based approach. This report offers recommendations for XR optical designers to identify the necessary diopter modulation for the target user population. The Weibull distribution is employed to model the refractive error distributions for these groups. The feasibility of this method in addressing high-order visual aberrations has been demonstrated. Comparisons are made among three demonstrated different populations (the United States, Europe, and China) to illustrate the minimum diopter requirements needed to accommodate various percentages of the population. The results of the study reveal that approximately 6 diopters are required to cover 90% of the general populations in both the United States and Europe. In contrast, the younger population in China requires an 8-diopter correction to achieve the same coverage percentage. This study not only underscores the utility of Weibull distribution in modeling refractive errors across different regional populations but also provides a compelling, evidence-based rationale for XR designers regarding the necessity of accommodating optics.
Mode separability in offset-based MGDM MMF links: a phase-retrieval-based approach
Authors: Ojha Komal , Appaiah Kumar
Published: October 2024

Mode group diversity multiplexing (MGDM)-based multimode fiber (MMF) systems have been known to be promising solutions for high-data-rate links. However, the challenge of cross-talk within these systems remains a critical concern, since coupling across mode groups diminishes data rates. Past work has shown that optimizing launch conditions and effective spatial filtering can minimize cross-talk across mode groups, although the optimization of the launching has been largely using trial-and-error-based approaches. Characterizing cross-talk limits and quantifying mode coupling requires the use of coherent imaging of the fiber, which is prohibitively complex. In this paper, we present, to our knowledge, a novel approach to characterize the received spatial signal at the MMF output, by obtaining both the amplitude and phase, using just imaging intensity measurements. This is enabled by leveraging recent advances in signal processing to recover the phase from intensity measurements using an alternating minimization-based algorithm for low-complexity phase retrieval, and presents an accurate characterization of mode coupling and estimation of cross-talk in MMF MGDM systems. Experimental validation demonstrates the effectiveness of this approach, particularly in offset-launch-based large-core MMF MGDM systems, where optimal launch parameters are identified to minimize cross-talk. Our findings highlight the significance of optimal launching and spatial filtering in maximizing mode separation, thus reducing cross-talk and enhancing overall system performance, as validated through extensive data rate experiments. The novel phase-retrieval-based fiber characterization can be extended and used to efficiently design spatial filtering solutions for MGDM, such as photonic lanterns and mode multiplexers.
Dynamical channel coupling in strong-field ionization of CO2
Authors: Zhu Yalei , Jiang Zeyu , Ren Zhongxue , Bai Guangru , Wang Xiaowei , Zhang Dongwen , Liu Jinlei , Zhao Jing , Zhao Zengxiu
Published: October 2024

We present a theoretical study employing the time-dependent density functional theory (TDDFT) to explore the effects of angle-resolved channel coupling in strong field ionization of carbon dioxide (CO2) molecules. Our results reveal significant angular sensitivity of both the channel-resolved ionization probabilities and the effects of laser-induced channel couplings. By applying a linearly polarized two-color field scheme, we demonstrate the ability to significantly modify the strength of the laser-induced coupling, evidenced by the changes in the population distributions among the ionic states induced by the strong-field ionization. Importantly, the two-color field optimally modulates the coupling strength at the alignment angle where ionization of the highest occupied molecular orbital (HOMO) electrons is most efficient. This optimization is attributed to the reduction of the electron shielding effect. Our research provides valuable insights into the coherent manipulation of electron distribution within the cation, paving the way for the precise control of ultrafast electron dynamics during strong-field ionization processes.
Steering high-Q intrinsic chiral quasi-bound states in the continuum via engineered 2.5D phase-change metasurfaces
Authors: Ouyang Siyuan , Sang Tian , Jing Ze , Lu Junjian
Published: October 2024

High-Q intrinsic quasi-bound states in the continuum (QBICs) require three-dimensional (3D) geometries with both in-plane and out-of-plane mirror symmetry breakings, hindering practical implementations due to the complex architectures. Here we demonstrate that high-Q intrinsic QBICs can be flexibly controlled by using the engineered 2.5D phase-change metasurfaces of Ge2Sb2Te5 (GST). By introducing the additional out-of-plane perturbations of slant angle θ and azimuthal angle φ, highly efficient and high-Q intrinsic circular dichroism (CD) for both reflection and transmission can be realized. The spinning-selected magnetic dipole (MD) is responsible for the high-Q intrinsic chirality. The high-Q intrinsic CD is robust to the variation of structural parameters, and its Q-factor and resonance location can be tuned through the phase transition of GST.
Parallel high-speed random bit generation based on wideband chaotic microcomb and wavelet high-pass filtering
Authors: Li Anran , Jiang Ning , Geng Yong , Qian Jiahao , Fang Yingjun , Zhang Qiang , Zhai Buqian , Xu Bo , Qiu Kun
Published: October 2024

We propose and experimentally demonstrate a parallel ultra-fast random bit generation (RBG) scheme based on wideband chaotic microcomb, which utilizes a phase modulation and dispersive component broadening spectrum. The effective bandwidth of each comb tooth is increased by over 10-fold. Wavelet high-pass filtering (WHPF) is employed to make the probability density functions (PDFs) of the chaotic signal’s amplitude unbiased, achieving high symmetry with a skewness coefficient |S| of 0.0026, and the RBG rate of a single channel reaches 200 Gbps. Furthermore, the autocorrelation properties of the random sequences from each comb tooth and the cross-correlation properties between different comb teeth are analyzed, confirming both true randomness and orthogonality. This scheme can simultaneously generate dozens of wideband chaotic combs in the wavelength range of 1500–1600 nm.
Lift-Off for Space Lasers
Authors: Cartlidge Edwin
Published: October 2024

Optical technology is set to transform communication from Earth orbit and beyond, although problems on the ground still need ironing out.
Decolonising humanitarian health: A scoping review of practical guidance
Authors: Clarke Amber , Richter Katharina , Lokot Michelle , Rivas Althea-Maria , Hafez Sali , Singh Neha S.
Published: October 2024

Despite growing calls and efforts to decolonise global and humanitarian health, there is limited practical guidance for researchers, educators and practitioners on how to do so. This paper fills this gap by offering a narrative exploration of key recommendations on decolonising global/humanitarian health research, partnerships, teaching, organisational structures and other practices. We present concrete guidelines to support humanitarian actors in decolonising their work. We used a scoping review method. The search strategy was built on three overarching themes: decolonising, global health/health and humanitarian crises. We combined a MEDLINE and Web of Science database search with a grey literature search. In total, we screened abstracts and titles of 533 documents, excluding records that did not specifically refer to ‘decolonising,’ humanitarian and/or global health. We assessed full texts of 58 documents for eligibility, excluding documents that did not include practical recommendations. In total, 15 documents were included in this review. We identified five key themes: organisational structure, strategy and engagement; research partnerships and conceptualisations; funding for research and projects; the research lifecycle; and teaching and the curriculum. The principal finding is that humanitarian actors can decolonise their work by decentralising power, redistributing resources, critically reflecting on their work in the context of the broader socio-political landscape and recovering, centring and valuing marginalised Global South perspectives. Race was not a central analytical category in the reviewed literature, despite being an integral part of historical background narratives. Future research should reflect on practical steps towards racial justice in global/humanitarian health and be focused on ensuring that efforts towards “localisation” or “equitable partnerships” in global health are linked to decolonisation efforts, including in humanitarian health research. Our review underscores the importance of drawing on knowledge created by and for actors based in the Global South.
Predictors of antenatal care services utilization by pregnant women in Afghanistan: Evidence from the Afghanistan Health Survey 2018
Authors: Stanikzai Muhammad Haroon , Tawfiq Essa , Suwanbamrung Charuai , Wasiq Abdul Wahed , Wongrith Paleeratana
Published: October 2024

Background

Poor utilization of maternal healthcare services remains a public health concern in most low and middle-income countries (LMICs), including Afghanistan. Late, inadequate, or no utilization of antenatal care (ANC) services pose a great concern.

Objectives

This study assessed the predictors of ANC service utilization among Afghan pregnant women, using secondary data from the Afghanistan Health Survey 2018 (AHS2018).

Methods

In this study, we used data from 10,855 ever-married women, aged 13–49 years, who gave birth in the two years prior to the survey or those women who were currently pregnant. The outcome variable was defined as a binary variable on ANC utilization (≥1 ANC visit equals 1, and zero otherwise). We fitted a binary logistic regression model and examined the associations between ANC utilization and explanatory variables, providing findings based on univariate and multivariate analysis. STATA version 17 was employed for the data analysis.

Results

Overall, 63.2%, 22.0%, and 3.1% of women had at least one ANC visit, ≥4 ANC visits, and ≥8 ANC visits during their last pregnancy, respectively. Higher odds of ANC utilization were observed in women who could read and write (AOR = 1.55, 95%CI: 1.36–1.77), whose husbands could read and write (AOR = 1.42, 95%CI: 1.29–1.56), who knew 1 sign (AOR = 1.93, 95%CI: 1.74–2.14), 2 signs (AOR = 2.43, 95%CI: 2.17–2.71) and ≥ 3 signs (AOR = 1.55, 95%CI: 1.36–1.77) of complicated pregnancy, and those with almost daily access to radio (AOR = 1.19, 95%CI: 1.08–1.327) and TV (AOR = 1.92, 95%CI: 1.73–2.13). We also found that women with one (AOR = 0.64, 95%CI: 0.49–0.84) and more than one (AOR = 0.60, 95%CI: 0.47–0.76) parity status, those for whom in-laws and others decided for their birthplace [(AOR = 0.85, 95%CI: 0.74–0.97) and (AOR = 0.63, 95%CI: 0.55–0.72), respectively], and those that resided in rural areas (AOR = 0.89, 95%CI: 0.79–1.00) had reduced odds of ANC utilization.

Conclusion

ANC service utilization is unacceptably low by pregnant women in Afghanistan. The predictors of ANC utilization identified by the study should be considered in the design of future interventions to enhance antenatal care utilization in Afghanistan.
Morphological encoding in language production: Electrophysiological evidence from Mandarin Chinese compound words
Authors: Wang Jiaqi , Schiller Niels O. , Verdonschot Rinus G.
Published: October 2024

This study investigates the role of morphology during speech planning in Mandarin Chinese. In a long-lag priming experiment, thirty-two Mandarin Chinese native speakers were asked to name target pictures (e.g., “山” /shan1/ "mountain"). The design involved pictures referring to morpheme-related compound words (e.g., “山羊” /shan1yang2/ "goat") sharing a morpheme with the first (e.g., “山” /shan1/ "mountain") or the second position of the targets (e.g., 脑 /nao3/ “brain” with prime电脑 /dian4nao3/ “computer”), as well as unrelated control items. Behavioral and electrophysiological data were collected. Interestingly, the behavioral results went against earlier findings in Indo-European languages, showing that the target picture naming was not facilitated by morphologically related primes. This suggests no morphological priming for individual constituents in producing Mandarin Chinese disyllabic compound words. However, targets in the morpheme-related word condition did elicit a reduced N400 compared with targets in the morpheme-unrelated condition for the first position overlap in the ERP analyses but not for the second, suggesting automatic activation of the first individual constituent in noun compound production. Implications of these findings are discussed.
Towards automatic farrowing monitoring—A Noisy Student approach for improving detection performance of newborn piglets
Authors: Wutke Martin , Lensches Clara , Hartmann Ulrich , Traulsen Imke
Published: October 2024

Nowadays, video monitoring of farrowing and automatic video evaluation using Deep Learning have become increasingly important in farm animal science research and open up new possibilities for addressing specific research questions like the determination of husbandry relevant indicators. A robust detection performance of newborn piglets is essential for reliably monitoring the farrowing process and to access important information about the welfare status of the sow and piglets. Although object detection algorithms are increasingly being used in various scenarios in the field of livestock farming, their usability for detecting newborn piglets has so far been limited. Challenges such as frequent animal occlusions, high overlapping rates or strong heterogeneous animal postures increase the complexity and place new demands on the detection model. Typically, new data is manually annotated to improve model performance, but the annotation effort is expensive and time-consuming. To address this problem, we propose a Noisy Student approach to automatically generate annotation information and train an improved piglet detection model. By using a teacher-student model relationship we transform the image structure and generate pseudo-labels for the object classes piglet and tail. As a result, we improve the initial detection performance of the teacher model from 0.561, 0.838, 0.672 to 0.901, 0.944, 0.922 for the performance metrics Recall, Precision and F1-score, respectively. The results of this study can be used in two ways. Firstly, the results contribute directly to the improvement of piglet detection in the context of birth monitoring systems and the evaluation of the farrowing progress. Secondly, the approach presented can be transferred to other research questions and species, thereby reducing the problem of cost-intensive annotation processes and increase training efficiency. In addition, we provide a unique dataset for the detection and evaluation of newborn piglets and sow body parts to support researchers in the task of monitoring the farrowing process.
Predicting adherence to gamified cognitive training using early phase game performance data: Towards a just-in-time adherence promotion strategy
Authors: Pang Yuanying , Singh Ankita , Chakraborty Shayok , Charness Neil , Boot Walter R. , He Zhe
Published: October 2024

Background and objectives

This study aims to develop a machine learning-based approach to predict adherence to gamified cognitive training using a variety of baseline measures (demographic, attitudinal, and cognitive abilities) as well as game performance data. We aimed to: (1) identify the cognitive games with the strongest adherence prediction and their key performance indicators; (2) compare baseline characteristics and game performance indicators for adherence prediction, and (3) test ensemble models that use baseline characteristics and game performance data to predict adherence over ten weeks.

Research design and method

Using machine learning algorithms including logistic regression, ridge regression, support vector machines, classification trees, and random forests, we predicted adherence from weeks 3 to 12. Predictors included game performance metrics in the first two weeks and baseline measures. These models’ robustness and generalizability were tested through five-fold cross-validation.

Results

The findings indicated that game performance measures were superior to baseline characteristics in predicting adherence. Notably, the games “Supply Run,” “Ante Up,” and “Sentry Duty” emerged as significant adherence predictors. Key performance indicators included the highest level achieved, total game sessions played, and overall gameplay proportion. A notable finding was the negative correlation between initial high achievement levels and sustained adherence, suggesting that maintaining a balanced difficulty level is crucial for long-term engagement. Conversely, a positive correlation between the number of sessions played and adherence highlighted the importance of early active involvement.

Discussion and implications

The insights from this research inform just-in-time strategies to promote adherence to cognitive training programs, catering to the needs and abilities of the aging population. It also underscores the potential of tailored, gamified interventions to foster long-term adherence to cognitive training.
AeroPath: An airway segmentation benchmark dataset with challenging pathology and baseline method
Authors: Støverud Karen-Helene , Bouget David , Pedersen André , Leira Håkon Olav , Amundsen Tore , Langø Thomas , Hofstad Erlend Fagertun
Published: October 2024

To improve the prognosis of patients suffering from pulmonary diseases, such as lung cancer, early diagnosis and treatment are crucial. The analysis of CT images is invaluable for diagnosis, whereas high quality segmentation of the airway tree are required for intervention planning and live guidance during bronchoscopy. Recently, the Multi-domain Airway Tree Modeling (ATM’22) challenge released a large dataset, both enabling training of deep-learning based models and bringing substantial improvement of the state-of-the-art for the airway segmentation task. The ATM’22 dataset includes a large group of COVID’19 patients and a range of other lung diseases, however, relatively few patients with severe pathologies affecting the airway tree anatomy was found. In this study, we introduce a new public benchmark dataset (AeroPath), consisting of 27 CT images from patients with pathologies ranging from emphysema to large tumors, with corresponding trachea and bronchi annotations. Second, we present a multiscale fusion design for automatic airway segmentation. Models were trained on the ATM’22 dataset, tested on the AeroPath dataset, and further evaluated against competitive open-source methods. The same performance metrics as used in the ATM’22 challenge were used to benchmark the different considered approaches. Lastly, an open web application is developed, to easily test the proposed model on new data. The results demonstrated that our proposed architecture predicted topologically correct segmentations for all the patients included in the AeroPath dataset. The proposed method is robust and able to handle various anomalies, down to at least the fifth airway generation. In addition, the AeroPath dataset, featuring patients with challenging pathologies, will contribute to development of new state-of-the-art methods. The AeroPath dataset and the web application are made openly available.
Combined use of Bacteria and Enzymes in the Degradation of Polymer Materials
Authors: Lisewska Daria , Mazuryk Alicja , Janczak Katarzyna
Published: October 2024

The development of the plastics industry, pro-ecological directives and environmental problems related to the decomposition of biodegradable plastics create necessity to develop a way to properly manage waste from materials that should not be deposited in the environment.
A bioproduct has been developed to be used for accelerating the biodegradation of polymer materials. The bioproduct includes carefully selected microorganisms and enzymes. It has been observed that metabolic activity of selected bacteria increases significantly in the presence of plastic material, causing degradative changes. In addition, enzymes were used that also stimulate the decomposition of polymer materials. Impact of bacteria and enzymes on polymer biodegradation was analyzed using different methods: BOD, mass loss, SEM-EDX and FTIR-ATR. Also the effect on plant growth was examined.
Five bacterial strains were selected as the active ingredients of the bioproduct, including two bacterial strains from the designated collection and three isolated from environment. Four hydrolytic enzymes have been selected that have the potential to accelerate the decomposition of polymer materials.
 
 
Keywords: bacteria, enzymes, biodegradation, polymer materials
CO2 Capture via Adsorption Using Silica Gel
Authors: Pérez-Rial Leticia , Alfonsín Víctor , Maceiras Rocío , Feijoo Jorge , P. Vallejo Javier
Published: October 2024

This paper investigates the potential of silica gel as an effective adsorbent for CO2 capture. The study explores the adsorption mechanisms, the efficiency of CO2 uptake, and some factors influencing the adsorption capacity of silica gel. The experimental results demonstrate the significant potential of silica gel for CO2 adsorption under various conditions. The adsorption capacity was found to be highly dependent on parameters such as gas flow rate and the particle size of silica gel. The findings suggest that with optimized conditions, silica gel could be a viable material for reducing atmospheric CO2 levels. This research contributes to the development of sustainable and efficient technologies for mitigating climate change through carbon dioxide capture and storage.
 
 
Keywords: CO2 capture, adsorption, efficiency, silica gel
Accelerators and Decelerators of Scaleup Growth: Key Factors and Circumstances for Sustainable Expansion
Authors: Slávik Štefan , Mišúnová Hudáková Ivana , Bednár Richard , Hajduová Zuzana
Published: October 2024

Scaleup is the development phase of a start-up that has solved its initial problems and is facing the challenge of achieving significant business rise and growth. However, it is still a small company whose growth is not easy. The goal of the research is to deepen and expand knowledge about the circumstances and factors that accelerate and/or slow down its growth. The source of new knowledge is field research on a sample of 97 scaleups. Researchers have personal experience from guided interviews with scaleup founders, which they recorded in the questionnaire. Respondents' statements were analyzed using critical discourse analysis (CDA) with the support of artificial intelligence. The result of the research is the identification of external growth accelerators, external growth decelerators, internal growth accelerators, and internal growth decelerators of scaleups. Each group of factors influencing growth contains five factors, the order of which corresponds to the weight of their positive or negative impact on growth. In addition, other accompanying circumstances affecting growth were similarly identified. The acquired knowledge can be used to evaluate the growth possibilities of a particular scaleup and to implement corrective measures according to the external and internal possibilities of the company. The research revealed an original and complex structure of factors and circumstances that influence the growth of scaleups and thus contribute to improving strategic thinking in this type of enterprise.
 
 
Keywords: scaleup, accompanying circumstances of growth, external and internal growth accelerators, external and internal growth decelerators.