bluuebunny/crossref_metadata_2025 huggingface dataset:
Coevolution and dynamic processes: an introduction to this issue and avenues for future research
Authors: Almudi Isabel , Fatas-Villafranca Francisco , Foster John , Potts Jason
Published: November 2024

In this paper, drawing upon previous contributions to modern Schumpeterian economics, we argue that coevolution in economic systems operates when considering several evolving populations within a socio-economic system, these populations mutually shape their respective selection, learning, and/or novelty generation mechanisms. The properties that arise from coevolution should be analyzed as emerging from multiple populations in co-determination. The notion of coevolution appears not only in Schumpeterian economics but, in general, in many branches of heterodox thought. Likewise, it can also be found in Biology, Sociology, Political Science, History, Philosophy, Law, and Computational studies. In this introduction, after providing a neat definition of coevolution, we illustrate with formal examples how coevolution can be represented and, potentially, empirically tested. Finally, we present the contributions to the SI and suggest avenues for future research.
Investigating spatial and temporal characteristics and elements influencing running among residents of Nanchang city in green open areas
Authors: Fang Tianwei , Zhou Linguo , Cai Zhenrao , Tan Zhijin , Chen Chao , Zheng Jiali , Fang Chaoyang
Published: November 2024

Understanding the exercise behaviors of urban residents in green open spaces is crucial for optimizing future urban spatial planning and improving residents’ quality of life. This study provides an in-depth analysis of residents’ running behaviors across 87 green open spaces in Nanchang City. Running data collected from the exercise platform Keep, coupled with urban geographic data and field research, reveals the spatial distribution and temporal variations of running activities, including running flow, distance, time, and pace. A set of indicator systems, such as total area, landscape form index, surrounding residential land area, and road conditions, is used to analyze its relationship with the environmental elements of green open spaces. The research results show that the running flow, running distance, and running time in green open spaces in Nanchang City are significantly influenced by different objective elements, while running pace shows little correlation with these environmental elements. Specifically, the study highlights the significant impact of elements such as total area and road length, as well as the number of nearby bus stops and population density, on residents’ running behaviors in Nanchang City’s green open spaces.
Enhancing Expert Decision-Making for Wastewater Treatment Plants with Seidel Laplacian Energy and Cosine Similarity Measure in Intuitionistic Fuzzy Graphs
Authors: Atheeque A. Mohamed , Basha S. Sharief
Published: November 2024

Wastewater treatment facilities’ main goal is to protect the public and environment from the hazardous and poisonous materials found in wastewater. Water treatment facilities were developed to speed up the natural process of cleansing water. A novel cosine similarity measure across intuitionistic fuzzy graphs has been proven to be more effective than certain present ones in group decision-making issues using example verification. This paper provides a unique approach for calculating expert-certified, well-known scores by finding the ambiguous information of intuitionistic fuzzy preference relations as well as the regular cosine similarity grades from one separable intuitionistic fuzzy preference relation to another. The new technique considers both "objective" and "subjective" information provided by experts. Using intuitionistic fuzzy preference relations, we provide workable techniques for judging experts’ eligible reputational ratings. This can be used to raise or decrease the relevance of the stated criteria in an evaluation that takes into account several competing elements. We give a solution to a decisional problem by using two effective methods: the newly constructed cosine similarity measure and the Seidel Laplacian energy (SLe+) of an intuitionistic fuzzy graph. Finally, two working procedures and circumstances are offered to show the effectiveness and superiority of the proposed techniques.
Random Oversampling-Based Diabetes Classification via Machine Learning Algorithms
Authors: Ashisha G. R. , Mary X. Anitha , Kanaga E. Grace Mary , Andrew J. , Eunice R. Jennifer
Published: November 2024

Diabetes mellitus is considered one of the main causes of death worldwide. If diabetes fails to be treated and diagnosed earlier, it can cause several other health problems, such as kidney disease, nerve disease, vision problems, and brain issues. Early detection of diabetes reduces healthcare costs and minimizes the chance of serious complications. In this work, we propose an e-diagnostic model for diabetes classification via a machine learning algorithm that can be executed on the Internet of Medical Things (IoMT). The study uses and analyses two benchmarking datasets, the PIMA Indian Diabetes Dataset (PIDD) and the Behavioral Risk Factor Surveillance System (BRFSS) diabetes dataset, to classify diabetes. The proposed model consists of the random oversampling method to balance the range of classes, the interquartile range technique-based outlier detection to eliminate outlier data, and the Boruta algorithm for selecting the optimal features from the datasets. The proposed approach considers ML algorithms such as random forest, gradient boosting models, light gradient boosting classifiers, and decision trees, as they are widely used classification algorithms for diabetes prediction. We evaluated all four ML algorithms via performance indicators such as accuracy, F1 score, recall, precision, and AUC-ROC. Comparative analysis of this model suggests that the random forest algorithm outperforms all the remaining classifiers, with the greatest accuracy of 92% on the BRFSS diabetes dataset and 94% accuracy on the PIDD dataset, which is greater than the 3% accuracy reported in existing research. This research is helpful for assisting diabetologists in developing accurate treatment regimens for patients who are diabetic.
Insights into Algorithmic Decision-Making Systems via a Decolonial-Intersectional Lens: A Cross-Analysis Case Study
Authors: Alba Joel Tyler
Published: November 2024

As the line between governance, technology, and decision-making becomes ever-blurred, advocates and disparagers of Artificial Intelligence (AI) debate the impacts of its societal integration. Despite efforts to promote Fairness, Accountability, Transparency, and Ethics (FATE), vulnerable populations continue to be systematically marginalized and made “invisible” by the racialised, classed, and colonial institutions buttressing Algorithmic Decision-Making Systems (ADMS). To address these sociotechnical risks and acknowledge our privileged, Western “standpoint epistemology,” we employ a “metaparadigm perspective” to engage the literature and case studies through a critical theory lens. The cross-analysis of three case studies: Systems Theory, the United States’ “Blueprint for an AI Bill of Rights,” and predictive policing demonstrate that our current risk mitigation frameworks are incapable of addressing transhistorical injustices. Therefore, we call for operationalizing intersectional risk theory via the decolonial turn to address ADMS risks. On that note, we propose three algorithmic accountability recommendations. We theorize that through a reformulation of FATE principles to that of the algorithmic (decolonial) self, understanding power imbalances through marginalized risk discourses, and advancing intersectional ML decision-making practices, policymakers may be better positioned to enact equitable and just ADMS.
Insights for the immunotherapy in malignant melanoma: a new revolution
Authors: Xuan Jiangying , Gao Zixu , Wei Chuanyuan , Gu Jianying
Published: November 2024

Melanoma is highly malignant and mainly occurs in the skin. Melanoma was first used in immunotherapy due to its high immunogenicity, which changed the therapeutic pattern of tumor patients. However, many patients do not benefit from immunotherapy because of its side effects, resistance and low sensitivity to anti-tumor responses. Recently, with a deeper understanding of tumor development, immunotherapy has emerged as a new era. In this review, we first elucidate the effects of immunotherapy on the tumor microenvironment (TME) and the mechanisms involved, as well as how immune cells exert immune promoting or immunosuppressive effects on the impact of immunotherapy. Then we mention the latest progress in immunotherapy of immune checkpoint blockades, such as CTLA-4, PD-1/PD-L1, TIM3 and LAG3. Biotherapies such as adoptive therapy, RNA vaccines and oncolytic virus are also included. Next, we elaborate on the problems and existing data of immunotherapy to explain the current clinical situation. To address these challenges, we introduce the combination strategies such as targeted therapy, radiotherapy, chemotherapy, and biotherapy. Numerous clinical data have showed that the combined treatment can significantly improve the therapeutic effect of melanoma patients. Overall, understanding the specific introduction of immunotherapy in melanoma may provide fresh perspectives for scientists to investigate therapeutic targets and identify new treatments.
Machine learning in neuroimaging of epilepsy: a narrative review
Authors: Perillo Teresa , Perillo Sandra , Pinto Antonio
Published: November 2024

Epilepsy is defined as a disorder of the brain characterized by an enduring predisposition to epileptic seizures. It is a heterogeneous condition characterized by multiple seizure types and syndromes, numerous etiologies, and variable prognoses. Neuroimaging plays a crucial role in the evaluation of epilepsy, with magnetic resonance imaging being the best imaging modality to diagnose epileptogenic lesions. In recent years, Machine Learning has proved to be useful in epilepsy to enhance diagnosis and treatment. Aim of this review is to describe the most recent advanced of Machine Learning in Epilepsy.
Recommendations on Imaging in the Context of Alzheimer’s Disease-Modifying Therapies from the CCNA Imaging Workgroup
Authors: Duchesne Simon , Collins D. Louis , Barlow Laura , Bartha Robert , Black Sandra , Chertkow Howard , Dadar Mahsa , Joshi Manish , Rosa-Neto Pedro , Soucy Jean-Paul , Smith Eric E.
Published: November 2024

Background:

Disease-modifying therapies (DMTs) for Alzheimer’s disease (AD) are emerging following successful clinical trials of therapies targeting amyloid beta (Aβ) protofibrils or plaques. Determining patient eligibility and monitoring treatment efficacy and adverse events, such as Aβ-related imaging abnormalities, necessitates imaging with MRI and PET. The Canadian Consortium on Neurodegeneration in Aging (CCNA) Imaging Workgroup aimed to synthesize evidence and provide recommendations on implementing imaging protocols for AD DMTs in Canada.

Methods:

The workgroup employed a Delphi process to develop these recommendations. Experts from radiology, neurology, biomedical engineering, nuclear medicine, MRI and medical physics were recruited. Surveys and meetings were conducted to achieve consensus on key issues, including protocol standardization, scanner strength, monitoring protocols based on risk profiles and optimal protocol lengths. Draft recommendations were refined through multiple iterations and expert discussions.

Results:

The recommendations emphasize standardized acquisition imaging protocols across manufacturers and scanner strengths to ensure consistency and reliability of clinical treatment decisions, tailored monitoring protocols based on DMTs’ safety and efficacy profiles, consistent monitoring regardless of perceived treatment efficacy and MRI screening on 1.5T or 3T scanners with adapted protocols. An optimal protocol length of 20–30 minutes was deemed feasible; specific sequences are suggested.

Conclusion:

The guidelines aim to enhance imaging data quality and consistency, facilitating better clinical decision-making and improving patient outcomes. Further research is needed to refine these protocols and address evolving challenges with new DMTs. It is recognized that administrative, financial and logistical capacity to deliver additional MRI and positron emission tomography scans require careful planning.
Monitoring-supported value generation for managing structures and infrastructure systems
Authors: Kamariotis Antonios , Chatzi Eleni , Straub Daniel , Dervilis Nikolaos , Goebel Kai , Hughes Aidan J. , Lombaert Geert , Papadimitriou Costas , Papakonstantinou Konstantinos G. , Pozzi Matteo , Todd Michael , Worden Keith
Published: November 2024

To maximize its value, the design, development and implementation of structural health monitoring (SHM) should focus on its role in facilitating decision support. In this position paper, we offer perspectives on the synergy between SHM and decision-making. We propose a classification of SHM use cases aligning with various dimensions that are closely linked to the respective decision contexts. The types of decisions that have to be supported by the SHM system within these settings are discussed along with the corresponding challenges. We provide an overview of different classes of models that are required for integrating SHM in the decision-making process to support the operation and maintenance of structures and infrastructure systems. Fundamental decision-theoretic principles and state-of-the-art methods for optimizing maintenance and operational decision-making under uncertainty are briefly discussed. Finally, we offer a viewpoint on the appropriate course of action for quantifying, validating, and maximizing the added value generated by SHM. This work aspires to synthesize the different perspectives of the SHM, Prognostic Health Management, and reliability communities, and provide directions to researchers and practitioners working towards more pervasive monitoring-based decision-support.
Sanitary-Hygienic Research to Ensure State Sanitary-Epidemiological Surveillance in the Republic of Kazakhstan
Authors: Moldayazova Lyazzat , Shagatayeva Bibigul , Zhapalakov Baser , Utegenova Elmira , Amrin Meiram
Published: November 2024

Objective

There are numerous factors that impact human health. Sanitary and hygienic conditions in the workplace and living environments, the state of the environment, and nutrition levels play a significant role in determining environmental quality. An integral part is also the organization of effective treatment and preventive health care services for the population. The purpose of this study is to analyze the sanitary and hygienic situation in the Republic of Kazakhstan.

Methods

The methodological framework employed general theoretical methods, statistical analysis, and techniques for systematizing information.

Results

During the study, it was determined that in several cities, high levels of respiratory and skin morbidity are recorded, linked to elevated concentrations of dust, ammonia, hydrogen fluoride, and nitrogen dioxide. As a consequence of chemical contamination of drinking water sources, there is an escalation in the incidence of nephritis and hepatitis, an upsurge in the number of toxicosis cases among pregnant women, and congenital anomalies. The sanitary condition of settlements greatly impacts the development of satisfactory living conditions.

Conclusions

Therefore, this research holds significant practical relevance, and the findings can be utilized by specialists in relevant fields to analyze and address the identified problems, as safeguarding public health, development, and improvement of its protection system is currently becoming one of the paramount tasks.
The Pathophysiology of Injuries and Deaths Managed in Emergency Departments After Earthquake Disasters: A Narrative Review
Authors: Yilmaz Sarper , Tatliparmak Ali Cankut , Ak Rohat
Published: November 2024

Earthquakes cause devastating effects, resulting in the deaths of thousands of people each year. Understanding the full range of impacts, including fatalities, and the pathophysiological mechanisms underlying these effects is crucial for mitigating the aftermath of earthquakes. Therefore, this review aims to: delineate the critical golden time periods following earthquakes and identify the most effective responses and resilience factors during these periods; accurately define the terminology for injuries sustained post-earthquake; elucidate the basic pathophysiology of CRUSH injury-induced myopathy, one of the most significant pathologies in post-earthquake patient management; explore the role of nitric oxide (NO) mechanisms in crush injuries, which are believed to be fundamental to the “smiling death phenomenon” and represent the unseen part of the iceberg; and highlight the importance of the 3 main phenomena responsible for mortality—acidosis, coagulopathy, and hypothermia—during disasters. This comprehensive review, based on the latest literature, encompasses search and rescue, pre-hospital processes, emergency department procedures, and subsequent internal and surgical management algorithms.
Compellence by denial against armed groups: UN peacekeeping in Ituri, the Democratic Republic of the Congo
Authors: Ohnishi Ken
Published: November 2024

Peace operations are often deployed to countries where conflicts are effectively ongoing, with mandates to protect civilians and provide security. With the authorisation to use force beyond self-defence, peacekeepers are expected to exert military pressure on armed groups to induce them to abandon violence and join peace processes. Such an approach falls in the domain of compellence. Given that peace operations struggle to adapt to this new expectation, it is imperative to find effective ways of compelling armed groups. While studies on compellence agree on the effectiveness of denial-type pressure, its specific forms are highly context-dependent. What is the most effective way to achieve denial against armed groups in the context of peace operations? There are four such approaches: attrition, stronghold neutralisation, decapitation, and counter-coercion negation. A case study of peacekeeping by the United Nation in Ituri reveals that stronghold neutralisation and counter-coercion negation were especially important for compelling rebels to disarm. As existing studies have not examined the effectiveness of specific forms of denial in peace operations, the finding contributes significantly to the literature on compellence and peace operations.
The Many Faces of Birthing Freedom
Authors: Chadwick Rachelle
Published: November 2024

What would birth be like in a feminist world? In this essay, I explore this question, asking what feminist freedom means in relation to birthing. Engaging in an imaginative inquiry that is rooted in respect for plurality, I explore the multifaceted dimensions of what we, as feminists, are fighting for in relation to birth. Building on a diverse array of feminist theories and philosophies of freedom (including the work of Simone de Beauvoir, Drucilla Cornell, and Marilyn Frye) and inspired by the work of Iris Marion Young on the five faces of oppression, I outline five faces of birthing freedom, namely: (1) freedom from oppression, (2) freedom to labor, (3) freedom to be-in-relation, (4) freedom from violence, and (5) freedom to imagine. I argue that these faces are all necessary conditions for the realization of birthing freedom. At the same time, the five faces of birth freedom that I outline here are only provisional and are grounded in my specific standpoint. My approach recognizes plurality and is not meant to be exhaustive but rather hopes to spark imaginings, invite extensions and revisions, and initiate conversations.
A Note on the Āl-i Burhān of Bukhara and the Author of the Laṭāʾif al-aḏkār
Authors: Qaemmaqami Seyed Ahmadreza
Published: November 2024

The Āl-i Burhān, who held the religious leadership (ṣadāra) of Bukhara from the end of the fifth to the middle of the seventh century A.H. (eleventh to thirteenth century CE) and were the religious and secular leaders of the city, are known to us through a number of studies by Bartold, Qazvīnī, and Pritsak.1 However, at least two other pieces of information about this family's background are available in two recently published books that were not available to these scholars. The first book is al-Qand fī ḏikr ʿulamāʾ Samarqand (henceforth al-Qand) by ʿUmar ibn Muḥammad al-Nasafī (461‒537 A.H./1069‒1142 CE), and the other is Laṭāʾif al-aḏkār li-l-ḥużżār wa-l-suffār fī al-manāsik wa-l-ādāb (henceforth Laṭāʾif) by Muḥammad ibn ʿUmar ibn ʿAbd al-ʿAzīz (511–566 A.H./1117‒1170 CE), the greatest religious leader (ṣadr) of this family in the sixth century A.H. (twelfth century CE).2 The latter, precisely because it was written by the greatest and most powerful member of the family, contains some firsthand information about the family itself and the scholars of Bukhara that appears to be unique, and the former provides the most detailed extant information about the scholars who lived in Samarqand or visited that city until the mid-sixth century A.H. (twelfth century CE). Al-Qand also incidentally contains some information about the first ṣadr of the Burhān family, which has neither been seen elsewhere nor noticed by scholars since the publication of the text in 1999.
Measurement of snowpack density, grain size, and black carbon concentration using time-domain diffuse optics
Authors: Henley Connor Andrew , Meyer Colin Richard , Chalif Jacob Ian , Hollmann Joseph Lee , Raskar Ramesh
Published: November 2024

Diffuse optical spectroscopy (DOS) techniques characterize scattering media by examining their optical response to laser illumination. Time-domain DOS methods involve illuminating the medium with a laser pulse and using a fast photodetector to measure the time-dependent intensity of light that exits the medium after multiple scattering events. While DOS research traditionally focused on characterizing biological tissues, we demonstrate that time-domain diffuse optical measurements can also be used to characterize snow. We introduce a model that predicts the time-dependent reflectance of a dry snowpack as a function of its density, grain size, and black carbon content. We develop an algorithm that retrieves these properties from measurements at two wavelengths. To validate our approach, we assembled a two-wavelength lidar system to measure the time-dependent reflectance of snow samples with varying properties. Rather than measuring direct surface returns, our system captures photons that enter and exit the snow at different points, separated by a small distance (4–10 cm). We observe clear, linear correlations between our retrievals of density and black carbon concentration, and ground truth. For black carbon concentration the correlation is nearly one-to-one. We also find that our method is capable of distinguishing between small and large grain sizes.
Women's Movement: Sport, Feminism, and the Torch Relay of the 1977 National Women's Conference
Authors: Schultz Jaime
Published: November 2024

It made for a great photograph. Icons of the feminist movement, stars of women's sport, and amateur athletes joined in a show of solidarity, rallied around the torch that would inaugurate the 1977 National Women's Conference in Houston, Texas (Figure 1). It was the first federally funded meeting of its kind, and 20,000 people cheered the arrival of the flame and the illustrious if motley crew that bore it aloft. The moment was, according to the official proceedings, “one of the most dramatic features of the Conference.”
Jaak Panksepp’s primary emotions are associated with Diener’s global life satisfaction: How low arousal of the SADNESS/separation distress system could form the core of life satisfaction?
Authors: Davis Kenneth L. , Montag Christian
Published: November 2024

We compared Ed Diener’s Satisfaction With Life Scale (SWLS), which was designed as a purely cognitive measure of global life satisfaction, with the Affective Neuroscience Personality Scales 3.1, which provides self-report measures of Panksepp’s six primary emotions (excluding LUST), in two English-speaking samples: a main sample and a hold-out validation sample. Our data showed robust negative correlations between higher satisfaction with life and lower FEAR, lower SADNESS/Separation Distress, and positive associations (albeit less strong) between higher satisfaction with life and higher PLAY and SEEKING in both samples. The relationships between the SWLS and at least four of Panksepp’s primary emotions suggest Diener’s SWLS is not purely cognitive and includes a strong affective component. In addition, detailed analysis of the negative correlation between the SWLS and the ANPS 3.1 SADNESS scale provides insight into the importance of the low arousal end of the SADNESS/Separation Distress brain system and supports the idea of a continuum of psychological states from high SADNESS including loneliness and depression to low SADNESS psychological states characterized by social comfort, self-confidence, and social strength.
What Is Democracy?
Authors: Kahn Paul W.
Published: November 2024

Modern democracies, including the United States, rely upon three normative elements: (1) rights expressing the dignity of the citizen; (2) law expressing a commitment to public reason; (3) elections as the method of selecting representatives. In each dimension, citizens are to see a representation of themselves as popular sovereign. Morality and law are not matters to be resolved at the polls. Yet, popular opinion, supported by contemporary social sciences, tends to reduce democracy to the third element. On this view, the higher the voter turnout, the better the democracy. In an age in which we worry as much about majority, as minority, tyranny, this view is not credible. A mob at the polls is still a mob even if it is a majority. An exclusive focus on quantification represents a profound misunderstanding of the meaning of democracy. Democratic politics includes an interpretive practice across the moral and the legal dimensions. It relies as much on persuasion as on proof. Recovery of a vibrant democratic life requires a renewed appreciation of a public humanities, not as a pastime but as way of living.
Life and Fate and the Public Humanities in the Age of AI
Authors: Moran Joe
Published: November 2024

In his novel Life and Fate, Vasily Grossman imagines that we will one day engineer an artificial intelligence that will mimic humans in every way. In order to reproduce “the peculiarities of mind and soul of an average, inconspicuous human being,” however, the computer that houses it will have to be bigger than the Earth. This essay takes Grossman’s novel as the start and endpoint for a discussion about the role of the public humanities in the age of artificial intelligence (AI). The response of the humanities to the pervasive fatalism about an AI-driven future should be twofold. First, they can serve as an antidote to a credulous, amnesiac present which sees the future as already decided, with inexorable effects that we can only adapt to. Second, they can challenge the now pervasive view of intelligence as computational and algorithmic. The humanities refuse to see humans as codable, or as just part of the data stream. We should certainly study the ways in which AI is changing what it means to be human, but we should never lose sight of what is most astonishing, and uncopiable, about us.
Current conservation status and potential distribution under climate change of Michelia lacei, a Plant Species with Extremely Small Populations in Yunnan, China
Authors: Liu Yang , Cai Lei , Sun Weibang
Published: November 2024

Michelia lacei W.W. Smith, a magnolia species categorized as Endangered on the IUCN Red List, is subject to severe disturbance. We carried out field surveys and a review of literature records to present a detailed description of the current status of M. lacei. We then predicted the potential distribution of M. lacei under different climatic scenarios based on 60 occurrence records (53 recorded during our field surveys and 7 earlier records) and 19 bioclimatic variables from the WorldClim database. We selected 18 locations and four bioclimatic variables for model training. Temperature seasonality and annual temperature range were the most influential variables for predicting the potential distribution of the species. We used MaxEnt to model distribution under current climate conditions and four Shared Socioeconomic Pathway scenarios in four future time periods to determine the effects of future climate change on the habitat suitable for the species. We predict areas of moderately and highly suitable habitat will gradually decrease over time. We recommend increased in situ and ex situ conservation efforts to mitigate this habitat decline and protect populations of M. lacei.
Symmetric monoidal smash products in homotopy type theory
Authors: Ljungström Axel
Published: November 2024

In homotopy type theory, few constructions have proved as troublesome as the smash product. While its definition is just as direct as in classical mathematics, one quickly realises that in order to define and reason about functions over iterations of it, one has to verify an exponentially growing number of coherences. This has led to crucial results concerning smash products remaining open. One particularly important such result is the fact that the smash product forms a (1-coherent) symmetric monoidal product on the universe of pointed types. This fact was used, without a complete proof, by, for example, Brunerie ((2016) PhD thesis, Université Nice Sophia Antipolis) to construct the cup product on integral cohomology and is, more generally, a fundamental result in traditional algebraic topology. In this paper, we salvage the situation by introducing a simple informal heuristic for reasoning about functions defined over iterated smash products. We then use the heuristic to verify, for example, the hexagon and pentagon identities, thereby obtaining a proof of symmetric monoidality. We also provide a formal statement of the heuristic in terms of an induction principle concerning the construction of homotopies of functions defined over iterated smash products. The key results presented here have been formalised in the proof assistant Cubical Agda.
How Civil Resistance Improves Inclusive Democracy
Authors: Bogati Subindra , Firawati Titik , Pinckney Jonathan , Thurber Ches
Published: November 2024

When do political transitions lead to greater inclusion for groups historically excluded from power? Scholars and policymakers often assume the answer is simple: a transition will result in more inclusion when it ends in democracy. Yet this answer is incomplete at best, since many democracies systematically exclude women, particular ethnic groups, or lower economic classes from power. Using data on political transitions around the world from 1945 to 2014, this study shows that a political transition’s initiating force critically shapes post-transition political inclusion. When transitions are initiated through unarmed civil resistance campaigns they achieve greater advances in inclusion relative to other types of transition. We propose three mechanisms to explain this effect: civil resistance leads to greater continued mobilization and civic activism among the historically excluded, provides greater opportunities for elites from historically excluded groups to rise to positions of leadership in new regimes, and forges more pluralistic norms of political behavior.
Coloniality and contestations over academic freedom in Africa
Authors: Appiagyei-Atua Kwadwo
Published: November 2024

Like other regions of the world, academic freedom is on the decline in Africa. While there are some generic factors accounting for this phenomenon worldwide, others are fundamentally unique to the African context. These are related principally to the subject matter of coloniality of higher education on the continent. This study addresses these matters by, among others, discussing the origins of the university in pre-modern Africa and the place of academic freedom in it. This development is followed by the emergence of university education in Europe through the application of the liberal script and which contributed to the sidelining and eventual general demise of higher education institutions with their roots in pre-modern Africa. The work contends that while one may trace the origins of the university/academic freedom to Africa, academic freedom as it stands today is shaped by the liberal script with hardly any reference to the root of higher education in Africa. Therefore, the meaning, understanding and application of academic freedom do not reflect the realities of higher education in Africa. This work proposes the adoption of a relative universalist approach, as opposed to the liberal approach, which is clothed with universality, but in reality, it is a reflection of a European idea of academic freedom. This approach is considered necessary to reflect the African reality of academic freedom which will help to identify effective advocacy tools to promote and protect academic freedom in Africa and thereby make academic freedom more meaningful for application in the region.
Effect of environmental factors on seed germination and seedling emergence of weedy rice (Oryza sativa f. spontanea) in China
Authors: Zhang Zichang , Xue Jing , Gu Tao , Wang Hongchun , Chauhan Bhagirath Singh
Published: November 2024

Weedy rice (Oryza sativa f. spontanea Auct. ex Backer) is a troublesome annual weed from the Gramineae family and infests rice (Oryza sativa L.) fields globally, with a notable presence in China. However, limited information is available regarding the effects of diverse environmental factors on its germination and emergence. A better understanding of the seed biology and ecology of weedy rice is crucial for developing effective weed management strategies. Experiments were conducted to evaluate the effects of temperature, light, soil burial depth, wheat (Triticum aestivum L.) crop residue amount, salt stress, osmotic stress, and radiant heat on the germination and seedling emergence of weedy rice. Weedy rice exhibited robust germination (>98%) when exposed to varying day/night temperatures (20/15 to 35/30 C) and remained unaffected by light conditions. Seedling emergence was not influenced within the top 5-cm soil layer, where 100% of the seedlings emerged. However, emergence decreased as the soil burial depth increased, eventually resulting in no emergence from a burial depth of 11 cm. The soil burial depth required for 50% of the maximum emergence was 8.3 cm. Seedling emergence ranged from 97% to 100% across different amounts of the wheat straw residue cover (0 to 10,000 kg ha−1). The sodium chloride concentration and osmotic potential required for 50% were 230.8 mM and −0.5 MPa, respectively. No germination was observed when weedy rice seeds were exposed to >110 C pretreatment (radiant heat for 5 min), indicating that residue burning could reduce infestation of weedy rice. The insights gained from this study contribute valuable knowledge to enhance the integrated management of weedy rice in China.
Warming Leads to Lower Rice Quality in East Asia
Authors: Liu Xianfeng , Ciais Philippe , Makowski David , Liang Juan
Published: November 2024

Rice quality, which is intricately connected to market value and human nutrition, is sensitive to weather conditions. However, the relative importance of the different climatic factors is poorly understood, and the impact of climate change on rice quality has been little studied on a large scale. Here, using more than 35 years of rice quality data, we present the first effort to determine the key climate variables driving rice quality in China and Japan. Results show a significant decline in high quality rice rate (HRR, an indicator of rice quality), mainly driven by warm nighttime temperatures when they exceed a critical threshold estimated at 18°C and 12°C in China and Japan, respectively. Climate projections suggest a continuing decreasing trend in HRR under moderate and high emission scenarios by 2100. These findings emphasize the importance of breeding new heat tolerant cultivars to maintain stable rice quality in the future.
A Seismic Precursor 15 min Before the Giant Eruption of Hunga Tonga‐Hunga Ha'apai Volcano on 15 January 2022
Authors: Horiuchi Takuro , Ichihara Mie , Nishida Kiwamu , Kaneko Takayuki
Published: November 2024

The 15 January 2022, eruption at Hunga Tonga‐Hunga Ha'apai (HTHH) volcano started shortly after 4:00UTC. There had been noted unconfirmed precursory events. We analyzed seismometer data recorded in Fiji and Futuna, the closest stations operated during the eruption and located over 750 km away. We extracted Rayleigh waves and estimated their powers and source directions, assuming retrograde particle motions. We found a Rayleigh wave from the HTHH's direction about 15 min before the eruption onset. The arrival time difference of the Rayleigh wave between the two stations was consistent with that of the M5.8 earthquake during the eruption located beneath the HTHH. Referring to other seismic signals and satellite images, we concluded that the Rayleigh wave was the most significant eruption precursor with no apparent surface activity. Including our findings and results of previous studies, we propose a scenario of the beginning of the caldera‐forming eruption.
Compound Tropical Cyclone Heat (TC‐Heat) Hazard in Hong Kong: Amplifying Urban Heat Extremes With Storm Position‐Driven Peripheral Warming and Urban Footprint
Authors: Chang Jeffrey Man‐Hei , Lam Yun Fat , Wong Yat‐Chun , Hon Kai Kwong
Published: November 2024

Compound hazards involving tropical cyclones and extreme heat (“TC‐heat”) have rarely been examined in prior research. Peripheral subsidence associated with cyclones can warm an area to varying degrees, depending on the cyclone's strength and position. Meanwhile, the peripheral airflow also overwhelmed the land‐sea breeze circulation system in coastal cities and favored downwind urbanized heat advection on the Southern China coastline. Here, we systematically applied ERA5 global reanalysis data, local surface‐level observations, MODIS‐based land‐cover data and HYSPLIT backward trajectories to evaluate how the position of distant TCs may divert the monsoon system and foster the surface heat advection from upwind urban agglomerate amplifying air temperature in downwind coastline. The analysis suggests when a distant TC is situated in a favorable area (the vicinity of Taiwan and Luzon Strait) at roughly 500–1,250 km to the east of Hong Kong, it forms a unique meteorological condition which allows the surface heat transport from the Greater Bay Area to Hong Kong, reflecting that regional build‐up of heat could be an important mechanism for producing local heat extremes.
Regionally Coupled Climate Model ROM Projects More Plausible Precipitation Change Over Central Equatorial Africa
Authors: Tamoffo Alain T. , Weber Torsten , Abel Daniel , Ziegler Katrin , Cabos William , Sein Dmitry V. , Laux Patrick
Published: November 2024

Unraveling plausible future rainfall change (ΔPr) patterns is crucial for tailoring societies' responses to climate change‐induced hazards. This study compares rainfall projections from the regionally coupled ocean model (ROM) and its atmospheric component, the regional atmospheric model REMO, over Central Equatorial Africa (CEA). Both models are forced by the Earth system model MPI‐ESM‐LR following the Representative Concentration Pathway 8.5. Results reveal increased rainfall across most of CEA, with ROM projecting more widespread and intensified wetting than REMO, although REMO produces more precipitation under future conditions, underscoring the influence of historical biases on REMO's projection. Examining processes underpinning changes unveils strong controls of sea and land surface temperature changes in ΔPr differences between the two models. Specifically, ROM mitigates warming more over the Atlantic than over CEA landmass compared to REMO, inducing enhancement of the Congo Basin cell and increased precipitable water content through specific humidity, affecting deep convection. Both models project enhanced Sahel and Kalahari thermal lows, with ROM better depicting the Kalahari low's warmer nature than the Sahel low. The resulting temperature gradients strengthen the northern and southern shallow meridional Hadley overturning circulation. ROM simulates the wetter conditions than REMO, attributed to its weaker northern Hadley Cell, which restricts the likelihood of northward moisture divergence toward the Sahel. Additionally, differences in mid‐tropospheric moisture convergence differentiate between ROM and REMO's wetness relative to the historical period and under future conditions. ROM projections are more plausible, in association with the reliability of its added value under the historical climate and mechanisms underlying Δpr.
Exploring a Data‐Driven Approach to Identify Regions of Change Associated With Future Climate Scenarios
Authors: Labe Zachary M. , Delworth Thomas L. , Johnson Nathaniel C. , Cooke William F.
Published: November 2024

A key consideration for evaluating climate projections is uncertainty in future radiative forcing scenarios. Although it is straightforward to monitor greenhouse gas concentrations and compare observations with specified climate scenarios, it remains less obvious how to detect and attribute regional pattern changes with plausible future mitigation scenarios. Here we introduce a machine learning approach for linking patterns of climate change with radiative forcing scenarios and use a feature attribution method to understand how these linkages are made. We train a neural network using output from the SPEAR Large Ensemble to classify whether temperature or precipitation maps are most likely to originate from one of several potential radiative forcing scenarios. Despite substantial atmospheric internal variability, the neural network learns to identify “fingerprint” patterns, including significant localized regions of change, that associate specific patterns of climate change with radiative forcing scenarios in each year of the simulations. We illustrate this using output from additional ensembles with sharp reductions in future greenhouse gases and highlight specific regions (in this example, the subpolar North Atlantic and Central Africa) that are critical for associating the new simulations with changes in radiative forcing scenarios. Overall, this framework suggests that explainable machine learning could provide one strategy for detecting a regional climate response to future mitigation efforts.
Integrated Water Management Under Different Water Rights Institutions and Population Patterns: Methodology and Application
Authors: Gharib Ahmed A. , Arabi Mazdak , Goemans Christopher , Manning Dale T. , Maas Alexander
Published: November 2024

While numerous studies have investigated demand management policies as a means of mitigating the impacts of climate change and population growth, little attention has been given to the interaction of spatial population patterns and water institutions that affect water shortages. In this article, we develop a methodology to evaluate how population location under alternative water institutions and climate scenarios impacts water demands, shortages, and derived economic values. We apply this methodology to the South Platte River Basin (SPRB) in Northeastern Colorado under three scenarios with ∼1,800 simulations. Results suggest that while water rights institutions have a negligible impact on total volumetric shortages relative to climate change, they have substantial distributional and economic implications. Results also suggest that continuous population growth in upstream cities yields the lowest water shortages if per capita use decreases with urbanization. However, if we assume that per capita demands do not decrease with population density, an equal distribution of population to upstream and downstream regions yields the lowest water shortage and highest economic value. These findings indicate the need that planning efforts must account for return flows and development patterns throughout a watershed in order to reduce water shortages and promote economic prosperity.
Binary vector copy number engineering improves Agrobacterium-mediated transformation
Authors: Szarzanowicz Matthew J. , Waldburger Lucas M. , Busche Michael , Geiselman Gina M. , Kirkpatrick Liam D. , Kehl Alexander J. , Tahmin Claudine , Kuo Rita C. , McCauley Joshua , Pannu Hamreet , Cui Ruoming , Liu Shuying , Hillson Nathan J. , Brunkard Jacob O. , Keasling Jay D. , Gladden John M. , Thompson Mitchell G. , Shih Patrick M.
Published: November 2024

The copy number of a plasmid is linked to its functionality, yet there have been few attempts to optimize higher-copy-number mutants for use across diverse origins of replication in different hosts. We use a high-throughput growth-coupled selection assay and a directed evolution approach to rapidly identify origin of replication mutations that influence copy number and screen for mutants that improve Agrobacterium-mediated transformation (AMT) efficiency. By introducing these mutations into binary vectors within the plasmid backbone used for AMT, we observe improved transient transformation of Nicotiana benthamiana in four diverse tested origins (pVS1, RK2, pSa and BBR1). For the best-performing origin, pVS1, we isolate higher-copy-number variants that increase stable transformation efficiencies by 60–100% in Arabidopsis thaliana and 390% in the oleaginous yeast Rhodosporidium toruloides. Our work provides an easily deployable framework to generate plasmid copy number variants that will enable greater precision in prokaryotic genetic engineering, in addition to improving AMT efficiency.
A study of some psychological variables as predictors of COVID-19 vaccination anxiety among Faculty Members of Ain Shams University
Authors: Al Baseer Nashwa Abdel Monem , Shaheen Hayam Saber
Published: November 2024

The study aimed to investigate the relative contribution of each of psychasthenia, psychological flexibility, suggestibility, and conspiracy beliefs in predicting the anxiety of vaccination with the anti COVID-19 vaccine among faculty members at Ain Shams University (ASU). Examining the difference in the sample’s scores on the vaccination anxiety scale and its sub-factors according to the variables (age—chronic diseases—academic specialization—previous infection with COVID-19—gender), the sample of the study included 139 faculty members at Ain Shams University aged ranged from 23 to 78 years, with a mean of 49.52 years, and a standard deviation of 13.29 years. The vaccination anxiety scale, psychasthenia scale, psychological flexibility scale, suggestibility scale, and conspiracy beliefs scale were used to collect data. The results revealed that the variables of suggestibility and conspiracy beliefs significantly contribute to predicting the vaccination anxiety among faculty members at Ain Shams University. There is a significant difference in the average scores on the vaccination anxiety scale according to age, with the difference in favor of the age group less than fifty years, as well as according to the presence/absence of a previous infection with COVID-19, with the vaccination anxiety being higher for those who were previously infected. There has been no observed significant difference according to the presence/absence of chronic diseases or academic specialization.