bluuebunny/crossref_metadata_2025 huggingface dataset:
Indoor and ambient influences on PM2.5 exposure and well-being for a rail impacted community and implications for personal protections
Authors: Torres Ivette , Do Khanh , Delgado Andrea , Mourad Charlotte , Yu Haofei , Ivey Cesunica E
Published: November 2024

Higher air pollution concentrations can be observed near rail networks, local and highway automobile corridors, and shipyards. Communities adjacent to such sources are disproportionately exposed to air pollution from these stationary and mobile sources. One such community is West San Bernardino in California, where households are feet away from the Burlington Northern Santa Fe intermodal facility and are impacted by activities that are estimated to continuously emit air pollutants due to 24/7 operation. This study aimed to (1) quantify the impact of personal mobility and housing characteristics on daily PM2.5 exposures and well-being for West San Bernardino community members, and (2) develop individualized resilience plans for community collaborators to support future PM2.5 exposure reduction. Personal PM2.5 exposures were measured for community collaborators for seven consecutive days during three deployment periods: October 2021, January 2022, and March 2022. Indoor and ambient PM2.5 levels were also continuously measured for five households over six months using PurpleAir Classic monitors. Demographic and well-being data were collected upon recruitment and after each week of engagement, respectively. Personal exposures in home microenvironments were highest near the railyard and lower farthest away from the railyard. Home exposures were 40% higher on average compared to non-home microenvironments. Household PM2.5 had a higher-than-expected average infiltration factor of 0.55, and indoor 98th percentiles across the households far exceeded a healthy level at an average of 165 μg m3. Resilience plans featured summaries of personal data and recommendations for mitigating exposures. Results suggest that surrounding land use and residential building characteristics compound to worsen air pollution exposures beyond what is expected for exposures in non-industrialized areas. Findings prompt a call for stronger regulation, not only for emissions, but also for indoor air quality and zoning standards that specifically protect disproportionately impacted communities.
Quantizations of transposed Poisson algebras by Novikov deformations
Authors: Chen Siyuan , Bai Chengming
Published: November 2024

The notions of the Novikov deformation of a commutative associative algebra and the corresponding classical limit are introduced. We show such a classical limit belongs to a subclass of transposed Poisson algebras, and hence the Novikov deformation is defined to be the quantization of the corresponding transposed Poisson algebra. As a direct consequence, we revisit the relationship between transposed Poisson algebras and Novikov–Poisson algebras due to the fact that there is a natural Novikov deformation of the commutative associative algebra in a Novikov–Poisson algebra. Hence all transposed Poisson algebras of Novikov–Poisson type, including unital transposed Poisson algebras, can be quantized. Finally, we classify the quantizations of 2-dimensional complex transposed Poisson algebras in which the Lie brackets are non-abelian up to equivalence.
Similarity among quantum-mechanical states: analysis and applications for central potentials
Authors: López-García I , Angulo J C , López-Rosa S
Published: November 2024

The similarity of quantum-mechanical solutions for central potentials is analytically determined and numerically explored for arbitrary dimensionalities. The study here provided focuses on hydrogenic systems and the harmonic oscillator, in respective non-relativistic frameworks. A diversity of analytical expressions for the quantum similarity measure (QSM) and index (QSI) are provided. Relevant conclusions are derived from the analyses grounded on state quantum numbers, space dimensionality and on the role played by the main characteristic parameters of these systems, namely the nuclear charge in the hydrogenic case, and the angular frequency for the oscillator. For this purpose, a statistical analysis of the QSI values has been performed for a large number both of states and combinations of them in each system. Considering the factorization of QSI into a radial and an angular part, particular attention is paid to the individual contribution of each part in both systems.
The optimization of water tourism management in Sumber Maron, Malang and Umbul Ponggok, Klaten
Authors: Nuriana Rheznandya Luthfi , Wahyuni Amalia Putri , Pratama Meiji Nanda Harda , Triningsih Luly , Apriadi Deny Wahyu , Waskito
Published: November 2024

Water tourism is an eminent sector potential to build Indonesians’ welfare. Water tourist destination that can attract tourists today is Umbul Ponggok, located in Klaten, Central Java and Sumber Maron in Malang, East Java. Both tourist destinations have water-based tourism concept by utilizing surrounding natural environment and empowering local people in their management. Therefore, this research aims to compare the optimization of water tourism management based on natural environment and the community empowerment. This research used a qualitative research method with phenomenological approach to see holistic information on water tourism management developed in both tourist objects. The result shows that in its management, Umbul Ponggok keeps attempting to maintain natural conservation and pays much attention to natural conservation and surrounding environment. It is similar to that in Sumber Maron prioritizing natural environment aspect and likewise surrounding community empowerment. Sumber Maron always attempts to review all tourism activities. However, the management existing in Sumber Maron is still far below standard existing in Umbul Ponggok. Therefore, the future tourism management should pass through some stages including trial, update, and public and village government participation to support the advancement of water tourism.
Social and Economic Aspects of The Scavengers at The Waste Disposal Site in Sandakan Sabah Malaysia
Authors: Mapa Mohammad Tahir Bin , Sahido Mohammad Haffizi Adam Bin , Jafar Adi , Sakke Nordin
Published: November 2024

Solid waste management is a pressing global issue, particularly in Malaysia, where population growth has led to increased waste generation, especially in urban areas. Landfills, while unavoidable, have inadvertently created job opportunities for individuals struggling to find employment in the formal job market. This study focuses on a group known as “scavengers,” who collect recyclable materials as a means of livelihood. The primary aim is to explore the social and economic conditions of scavengers at the Sandakan District Council garbage disposal site, located adjacent to Kg Melayu. Through in-depth interviews with thirty respondents, the research reveals that many scavengers are illegal undocumented, often working in groups, whether related or not. The findings indicate that their working conditions expose them to harsh weather, impacting their health. Economically, scavengers sell the collected materials daily, which is crucial for their sustenance. The study emphasises the need for local authorities to consider the role of scavengers in waste management planning to enhance recycling efforts in the district.
Utilization of Muria Strait Toponymy data in mitigation: Building resilience to disaster risk
Authors: Wahyudi Deny Yudo , Purnawan Jati Slamet Sujud , Wijaya Daya Negri , Azda Laili Vita Sabrina , Ananda Labuda Shofiya , Ikhrom Anisa Musyaroful
Published: November 2024

The North Coast of Java Island, including the area around Kendal to Rembang (formerly known as the Muria Strait region), is susceptible to sea water rise and land subsidence, which pose a significant risk to the lives of its inhabitants. Similarly, the districts of Demak, Kudus, Pati, Rembang, and Juwana are also vulnerable to these threats given that they were formed by alluvial deposits and are now densely populated. However, the community’s resilience to various changes in Muria Strait’s geosphere can be observed in the development of local knowledge, including toponymy. In the modern era, toponymic data can be used as instruments to support disaster mitigation and recovery efforts. The information content obtained after the toponymy study can be used as an instrument to increase public awareness and develop a targeted mitigation infrastructure. Given the community’s vulnerability to a range of disasters exacerbated by climate change, the objective of this research is to disseminate the findings of a toponym study of the Muria Strait, with a focus on the potential of these data to inform disaster-mitigation strategies. Toponymy data analysis was conducted using an ethnopedological approach in the context of archaeological and historical research. This approach was also necessary to analyse historical sources related to soil cover/land use (SLC) and changes in the geosphere of the Muria Strait over time.
Compression behavior of ex-situ PVC foam-filled tubes
Authors: Linul Emanoil , Vălean Cristina , Rusu Andreea-Iustina
Published: November 2024

The present work investigates the mechanical characteristics of tubes filled with Polyvinyl chloride (PVC) foam. The tubes used are made of aluminum and were filled ex-situ. Static compression tests were performed on both axially (AL) and laterally (LL) loaded tubes. Comparisons between foam-filled (FFT) and empty (ET) tubes are presented, highlighting the foam-tube interaction effect. The emphasis is on elastic, strength and strain properties, but energy absorption performances are not neglected. Discussions regarding the failure mechanisms of ETs and FFTs are also presented. It was obtained that, regardless of the loading direction, FFTs show clearly superior mechanical properties to ETs. At the same weight, the specimens tested axially support higher loads than those tested laterally. This aspect is due to deformation mechanisms that take place in the samples during the tests. It was noted that the compressive strength is more affected by the filling than by the compressive modulus. Under lateral loads, the ETs samples fail quasi-brittle through complete failure of the tube, while in the case of FFTs, a ductile fracture with stable deformation of the sample is obtained.
The possibility of recycling iron sludge in the steel industry
Authors: Bobora Adriana , Socalici Ana , Birtok Baneasa Corneliu , Sapta Doru
Published: November 2024

The steel industry strives to achieve quality steel with improved mechanical properties. In order to meet these market requirements, steel manufacturers need to streamline technological operations, increase process efficiency and productivity, and improve product quality control. Old iron and scrap metal used in the production of steel come from various sources and special attention should be paid to their quality, in particular, to the content of elements harmful to steel. The paper presents the results of the research undertaken on the use as raw material of the steel-making aggregates, in addition to the classic assortments of old iron of by-products obtained from the processing of iron slats in the form of briquettes. The influence of the quality of waste used was assessed by expanding the raw material base in the context of sustainable development, on steel blanks by investigating the effect on the chemical composition as well as the possibility of recovery of alloying element.
Study on the mechanical properties of Polyacrylic Acid/Chitosan double network hydrogels in dynamic water content
Authors: Gao Yang , La Huanjun , Min Haonan , Hou Zhenzhong
Published: November 2024

Hydrogels have demonstrated significant potential in wound dressings, owing to their adjustable water content, excellent biocompatibility, and other advantages. An ideal wound dressing requires absorbing exudate while maintaining mechanical properties to prevent secondary damage to the wound under external pressure. In this study, Polyacrylic Acid (PAA)/Chitosan (CS) double network hydrogels were prepared via radical polymerization, and the swelling ratio, compressive modulus, and other parameters were experimentally measured. A hyperelastic finite element model of the hydrogel was then established, and its rationality was validated by experiments. Based on the model, the impacts of CS content and dynamic water content on the compressive properties of PAA/CS hydrogels were analyzed. Tetracycline hydrochloride was loaded into PAA/CS hydrogels, the drug release performance and adhesion experiments were carried out. The results indicated that, compared with the hydrogels with 2.5% and 5% CS content, the hydrogel with 1% CS content had the highest swelling ratio, which was 1774%. Meanwhile, its equilibrium water content could attain 94.6%. When the water content varied within the range from 45% to 75%, the compressive strength of the hydrogel with 5% CS content ranged from 0.33 MPa to 1.22 MPa, similar to that of skin tissue. Additionally, the prepared drug-loaded PAA/CS hydrogels exhibited a drug release pattern approximately following the Korsmeyer-Peppas model within 7 days. They also exhibited remarkable adhesion to porcine skin and different substrate surfaces. This study provides a basis for the clinical application of PAA/CS double network hydrogels as wound dressings in the repair of infected wounds.
Freeze-necking and volumetric change of clay during freezing by 3D x-ray computed tomography
Authors: Fan Wenhu , Wang Jiaqi , Zhang Tao , Zuo Xi , Xiao Zhi , He Pengfei , Shi Xin
Published: November 2024

In artificial freezing engineering, the freezing temperature is an important factor affecting soil frost heave deformation, and studying its impact is of great significance. The frost heave ratio of soil is a crucial factor for designing and predicting soil frost heave. However, it only considers vertical deformation while neglecting radial deformation. This paper introduces a simple unidirectional freezing apparatus specifically designed for three-dimensional x-ray computed tomography (CT) scanning, which allows for the investigation of internal structural changes in clay during freezing at four different freezing temperatures (i.e., −3 °C, −5 °C, −7 °C, and −9 °C). Freeze-necking of the soil was observed during freezing. An image processing method was proposed to segment the soil samples, and parameters such as length, equivalent diameter, and volume were measured to assess changes during freezing. The observed variations in necking depth and equivalent diameter indicate that freeze-necking is uniform. As the freezing temperature decreased, the necking depth reduced from 72.4 mm to 38.1 mm, and within this necking depth, the equivalent diameter decreased progressively from the bottom to the top. Moisture content increased near the cold end of the soil and decreased near the warm end, suggesting that freeze-necking is due to moisture migration within the soil. Considering freeze-necking, the volumetric frost heave ratio was defined to characterize soil frost heave deformation. This ratio also decreases as the freezing temperature decreases, and the values are smaller than those of the traditional frost heave ratio. The discrepancies become more pronounced at higher freezing temperatures, reaching up to 1.8% at −3 °C. The results indicate that lower freezing temperatures can reduce frost heave deformation, and freeze-necking requires greater attention in engineering at higher freezing temperature.
Comparing the performance of a femoral shaft fracture fixation using implants with biodegradable and non-biodegradable materials.
Authors: Taghipour Sina , Vakili-Tahami Farid , Chakherlou Tajbakhsh Navid
Published: November 2024

Orthopedic injuries, such as femur shaft fractures, often require surgical intervention to promote healing and functional recovery. Metal plate implants are widely used due to their mechanical strength and biocompatibility. Biodegradable metal plate implants, including those made from magnesium, zinc, and iron alloys, offer distinct advantages over non-biodegradable materials like stainless steel, titanium, and cobalt alloys. Biodegradable implants gradually replace native bone tissue, reducing the need for additional surgeries and improving patient recovery. However, non-biodegradable implants remain popular due to their stability, corrosion resistance, and biocompatibility. This study focuses on designing an implant plate for treating transverse femoral shaft fractures during the walking cycle. The primary objective is to conduct a comprehensive finite element analysis (FEA) of a fractured femur’s stabilization using various biodegradable and non-biodegradable materials. The study assesses the efficacy of different implant materials, discusses implant design, and identifies the optimal materials for femoral stabilization. Results indicate that magnesium alloy is superior among biodegradable materials, while titanium alloy is preferred among non-biodegradable options. The findings suggest that magnesium alloy is the recommended material for bone implants due to its advantages over non-degradable alternatives.
A class alignment network based on self-attention for cross-subject EEG classification
Authors: Ma Sufan , Zhang Dongxiao , Wang Jiayi , Xie Jialiang
Published: November 2024

Due to the inherent variability in EEG signals across different individuals, domain adaptation and adversarial learning strategies are being progressively utilized to develop subject-specific classification models by leveraging data from other subjects. These approaches primarily focus on domain alignment and tend to overlook the critical task-specific class boundaries. This oversight can result in weak correlation between the extracted features and categories. To address these challenges, we propose a novel model that uses the known information from multiple subjects to bolster EEG classification for an individual subject through adversarial learning strategies. Our method begins by extracting both shallow and attention-driven deep features from EEG signals. Subsequently, we employ a class discriminator to encourage the same-class features from different domains to converge while ensuring that the different-class features diverge. This is achieved using our proposed discrimination loss function, which is designed to minimize the feature distance for samples of the same class across different domains while maximizing it for those from different classes. Additionally, our model incorporates two parallel classifiers that are harmonious yet distinct and jointly contribute to decision-making. Extensive testing on two publicly available EEG datasets has validated our model's efficacy and superiority.
Escalating threat of human-perceived heatwaves in Brazil
Authors: Ballarin André S , Oliveira Paulo Tarso S , Uchôa José Gescilam S M , Lima Carlos H R , Zaerpour Masoud , Godoy Mijael Rodrigo Vargas , Meira Neto Antônio A , Papalexiou Simon Michael , Wendland Edson
Published: November 2024

Heatwaves pose significant threats to socioeconomic and environmental systems, with their intensity and frequency expected to increase due to climate change. Despite their critical impacts, future heatwaves in Brazil remain underexplored, especially from a human-perceived perspective, which is crucial for assessing potential public health impacts. Here, we propose a method to assess heatwaves using the humidex (

H

)—a climate index that combines temperature and relative humidity to indicate human-perceived heat - alongside traditional temperature-based measures. Using bias-corrected simulations from 10 CMIP6 models under SSP2-4.5 and SSP5-8.5 scenarios, we quantified projected changes in heatwaves across Brazil. The results indicate that heatwaves will become more severe and prolonged, with greater changes under the SSP5-8.5 scenario by the end of the century, particularly in the North, Northeast, and Central regions. The magnitude of human-perceived heatwaves is expected to rise faster than temperature-based ones, underscoring the need for public health-focused assessments. CMIP6 models strongly agree on increased future heatwaves, potentially tripling population exposure in most Brazilian states, with the Southeast experiencing greater changes due to its larger population. These events are expected not only to affect more people but also to be more severe, exceeding over 60 days per year of serious danger (H > 45 °C) by the end of the century under SSP5-8.5. Record-shattering events in the historical period are projected to become the norm by mid-century, highlighting the accelerating nature of these extreme events. Our findings emphasize the importance of considering human-perceived heat in climate impact studies and public health planning to mitigate potential impacts. Significance Statement Despite the increasing threat of heatwaves, most studies focus on their climate properties, overlooking human-perceived aspects. This is especially true for Brazil, where heatwaves receive limited attention. This study introduces a novel approach, coupling heatwaves with a heat stress index (H) to evaluate them from a human-perceived perspective. Our results suggest more intense and prolonged heatwaves in the future, with record-breaking events becoming the norm by mid-century. Human-perceived heatwaves are projected to rise faster than climate-based ones, emphasizing the need for public health-focused assessments. These increases are expected to more than triple population exposure in most Brazilian states, with severe events (H > 45 °C) exceeding 60 days per year by the end of the century under the pessimistic scenario.
How could payments for U.S. climate-smart farming practices change the regional adoption of conservation practices?
Authors: Burnett J Wesley , Sichko Christopher , Gramig Benjamin M , Bowman Maria , O’Hara Jeffrey
Published: November 2024

Recent U.S. policies have promoted climate-smart farming practices. However, little is known about the costs of practice adoption or the regional allocation of support. The primary objective of this study is to identify cost-effective agricultural practices for climate mitigation and determine where practices might be targeted regionally. This study uses average regional abatement cost curves for six mitigation practices to analyze how conservation funding could incentivize adoption. Using a social benefit threshold of $51 per metric ton, we estimate that for all practices studied, except cover crops, there are regions where the average cost of reduction is less than the social benefit threshold, meaning that greenhouse gas could be cost-effectively mitigated or sequestered at regional levels given more adoption of these practices. For the purposes of conservation targeting, we outline the regions where the adoption of these practices is potentially the most cost-effective.
Land use change and its impact on ecosystem service value in Xinjiang
Authors: Hao Yifeng , Zhou Xindong , Shiyao Liu , Tao Wanghai
Published: November 2024

Xinjiang is an important hub connecting China and Eurasia and has an important strategic position in economy, energy, and ecological security. However, due to the fragile ecological environment in Xinjiang, there are substantial challenges in coordinating the relationship between social and economic development and ecological environment construction. To elucidate the relationship between land use changes induced by human activities and the valuation of ecosystem services, this study utilized the value equivalent method to evaluate the ecosystem service value in Xinjiang from 2000 to 2020 while analyzing its spatiotemporal response characteristics related to land use. The results showed that from 2000 to 2020, the value of ecosystem services in Xinjiang showed an upward trend, reaching 182.24 yuan/hm2 in 2020, and the total value of the whole region was 302.584 billion yuan. The value of ecological services in Xinjiang is mainly low-grade (about 50%), and high-grade only accounts for 1.03%~2.19%. There was a significant increase in land use in forested areas and water bodies, while the conversion trend from effective grassland to other land types was relatively limited. Specifically, 4.47% of bare ground and 3.76% of meadows transformed water bodies. Additionally, 2.69% of grassland experienced conversion into woodland. The land use intensity was generally low (more than 85% of the low-grade grades), and 83.71% of the land use intensity increased during the study period. The water area was the main controlling factor of the service value of the state system, with a contribution rate of 78.83%, followed by grassland (11.29%) and woodlands (9.30%), and 54.39% of the land use changes increased the value of ecosystem services.
The state and future of extreme heat studies in Southeast Asian megacities: risk, impacts and adaptation strategies in a warming world
Authors: Macagba Sharon Feliza Ann P , Delina Laurence L
Published: November 2024

Southeast Asian cities are increasingly affected by heat-related phenomena and various climate-related disasters; however, research on urban heat in this region remains limited compared to other areas. This paper employs bibliometric and thematic analyses to investigate studies on extreme heat in mega-urban areas of Southeast Asia, focusing on the risks and impacts faced by vulnerable populations and their adaptation and mitigation strategies. The bibliometric analysis visualises the research landscape, identifying key clusters and highlighting prevalent themes and gaps. It reveals a predominant emphasis on characterising extreme heat and analysing urban temperature variations through satellite and meteorological data, underscoring a significant lack of research on the socio-economic factors affecting at-risk communities. The thematic analysis further examines how existing studies address these socio-economic vulnerabilities and evaluates the adaptation strategies employed, particularly concerning land use changes driven by population growth. Our findings indicate that, while studies address urban heat in Southeast Asia, their quantity is relatively small compared to the extensive research focused on other regions. Strategies to mitigate the effects of extreme heat on mental and social well-being emphasise the importance of green infrastructure and public spaces. There is also a pressing need to enhance urban planning and design to ensure adaptation measures include at-risk, lower-income communities. Understanding the complexities of the risks and impacts of extreme heat on urban populations is crucial for developing effective, context-specific adaptation strategies that prioritise the needs of vulnerable populations and promote equitable, sustainable urban development.
Friction stir processed magnesium matrix surface composites: a comprehensive review
Authors: Kang Amardeep Singh , Singh Ravinder Pal , Singla Shivali , Kumar Abhinav
Published: November 2024

Nowadays modern materials are tailored using different manufacturing techniques. Usually, material surface is modified by even distribution of reinforcement particles/ fibres up to a certain depth. The developed surface metal matrix composites (MMCs) exhibit superior metallurgical, mechanical and electrochemical properties in contrast to base materials. These surface MMCs have potential applications in biomedical, automotive, aerospace and power industries. Many techniques have been used to develop these surface MMCs, however, the friction stir processing (FSP) has gained wide popularity. This review paper summarizes the effects of different FSP parameters on the metallurgical, mechanical and electrochemical properties of developed surface composites. Furthermore, the effects of secondary phase particles on the Magnesium-matrix surface composites are also comprehensively discussed.
SSDSNet: a dual-stream state-space network for efficient image denoising with long-range dependency modeling
Authors: Chen Ling , Xia Xun
Published: November 2024

In recent years, advancements in deep learning architectures such as Convolutional Neural Networks (CNNs) and Transformers have significantly enhanced the field of image denoising. Nevertheless, current denoising techniques often encounter challenges stemming from inherent local inductive biases or the quadratic computational demands of their designs. Recently, Selective Structured State Space Models, particularly exemplified by Mamba, have demonstrated substantial promise in capturing long-range dependencies with linear computational complexity. Despite their potential, these models have not been extensively explored for low-level computer vision applications. In this paper, we present the Dual-Stream State-Space Module (DSSM), a simple yet powerful model tailored for image denoising tasks. The DSSM integrates convolutional operations with the Mamba model, thereby enhancing the ability to extract both local features and global contextual information. This dual-stream framework effectively utilizes the structured nature of local image patches while adeptly modeling long-range interactions, resulting in feature representations optimized for denoising. Comprehensive experiments validate the efficacy of our approach. Notably, on the SIDD dataset, our model matches the performance of leading state-of-the-art methods, maintaining a global receptive field with comparable computational efficiency.
Calibrating Bayesian generative machine learning for Bayesiamplification
Authors: Bieringer S , Diefenbacher S , Kasieczka G , Trabs M
Published: November 2024

Recently, combinations of generative and Bayesian deep learning have been introduced in particle physics for both fast detector simulation and inference tasks. These neural networks aim to quantify the uncertainty on the generated distribution originating from limited training statistics. The interpretation of a distribution-wide uncertainty however remains ill-defined. We show a clear scheme for quantifying the calibration of Bayesian generative machine learning models. For a Continuous Normalizing Flow applied to a low-dimensional toy example, we evaluate the calibration of Bayesian uncertainties from either a mean-field Gaussian weight posterior, or Monte Carlo sampling network weights, to gauge their behaviour on unsteady distribution edges. Well calibrated uncertainties can then be used to roughly estimate the number of uncorrelated truth samples that are equivalent to the generated sample and clearly indicate data amplification for smooth features of the distribution.
Sexual Ethics and Problematic Consent
Authors: Boonin David
Published: November 2024

This book discusses cases where it’s unclear whether a person’s consent to sex should count as valid consent, the kind of consent that makes it permissible for the person they give consent to to have sex with them. Clear cases of coercion, for example, involve the threat of significant physical harm. But what should we say about cases involving the threat of harms that are relatively insignificant or that involve no physical harm at all? Impersonating someone’s spouse to trick them into saying yes to sex is clearly seriously wrong, but what about the more mundane kinds of lies people tell when they’re trying to meet someone? It’s wrong to have sex with someone who says yes when they’re so drunk they’re about to pass out and not wrong if they say yes after having a few sips of beer. What, though, should we say about the more difficult cases in the middle where it’s genuinely unclear whether they’ve had too much to drink? What’s the most reasonable view about other forms of incompetent consent to sex, like those involving young children, elderly dementia patients, or people born with severe and permanent cognitive impairments? And what about cases of problematic sexual consent that don’t involve coercion, deception, or incompetence at all? Can a patient give valid consent to sex with their therapist? Can the offer of a large amount of money in exchange for sex invalidate the sexual consent the offer elicits? This book addresses these and related questions.
Coercion and Sexual Consent
Authors: Boonin David
Published: November 2024

This chapter discusses three kinds of case where it’s unclear whether a person’s consent to sex is rendered invalid by coercion. In the first kind of case, one person threatens to inflict a significant non-physical harm on a second person if the second person does not consent to have sex with them (e.g., they threaten to break up with them or to reveal an embarrassing secret about them). The first section of this chapter argues that consent is valid in such cases if and only if the threatened harm is one that it would be permissible for the person to inflict on them. In the second kind of case, one person threatens to inflict an insignificant harm on a second person if the second person does not consent to have sex with them (e.g., a pinch on the arm or a minor inconvenience). The second section of this chapter argues that harms of any magnitude are sufficient to render a threat coercive as long as they’re harms the threatener has no moral right to inflict. In the third kind of case, one person threatens to inflict a significant harm on a second person if the second person does not give consent to a third person to have sex with that third person. The third section of this chapter argues that such third-party coercion from the first person does not invalidate the second person’s consent to have sex with the third person.
Incompetence and Sexual Consent
Authors: Boonin David
Published: November 2024

This chapter discusses four kinds of problem cases involving people who are, or who might be, incompetent to give valid consent to sex. The first section addresses intoxicated consent. It argues that the range of cases where it’s not sufficiently clear whether a person is too drunk to competently consent to sex is considerably larger than it might at first seem and that it’s wrong to have sex with someone when they’re intoxicated to such a degree even if they’re probably not too drunk to validly consent. The second section considers dementia and sexual consent. It argues that, under certain conditions, a competently signed sexual advance directive can make it permissible to have sex with someone who has subsequently developed dementia and argues that this position can plausibly be extended to some cases where no such directive was signed. The third section discusses pedophilia. It rejects the argument that says pedophilia is wrong because young children cannot currently give competent consent to sex and instead argues that it’s wrong because they can’t reasonably be expected to give their retroactive consent to it once they become competent adults. The fourth section addresses the case of people who are born with severe and permanent cognitive impairments. It argues, although tentatively, that under certain conditions, the sexual behavior of such people can count as a form of valid consent to sex or can at least play the same role that valid consent to sex plays.
Simplifying acquisition of essential diagnostics: A comprehensive costing tool for anatomic pathology
Authors: LeJeune-Stodieck Analise , Seymour Daniel , Graef Katy , Hategekimana Elisee , Mbarushimana Djibril , Ndayisaba Marie Claire , Pereira de Assis Emilio Augusto Campos , Yeabyo Girogis Okubazgi , Nweke Michael Chukwugozium , Berhane Bereket , Emmanuel Hakizimana , Ruhangaza Deo , Weber Callie , Basu Debby , Landgraf Kenneth , Milner Dan
Published: November 2024

Objectives

Histopathology is the core diagnostic tool for cancer in pathology laboratories around the world, but there are disparities in access to diagnostics globally. As recognition of the need for cancer care and treatment grows, especially in the wake of World Health Organization programs for cervical, breast, and pediatric cancers, policymakers and health care funders are seeking tools and processes that allow for the largest number of patients to receive a diagnosis at the lowest cost.

Methods

As histopathology represents the most cost-effective diagnostic method by sheer number of tumor types and volume, understanding the detailed logistics and costs for histology as well as the impactful benefits of economies of scale (ie, larger volumes are less expensive per patient) and scope (ie, the multiple stains available after basic histology sectioning) is paramount to planning an effective publicly funded or government laboratory. Understanding the economic structure of a country’s population along with the financial model of a histology laboratory also leads to a market understanding of private laboratories, which can provide services at a profit as well as pro bono services more cost-effectively than purely public laboratories.

Results

We have developed a comprehensive, scalable costing tool of a functioning histology laboratory that accounts for all feasible costs and variations in models of service. The tool allows for a standardized approach to selecting goods needed to provide histology services and serves as a guide for implementation of pathology services.

Conclusions

Using the tool, laboratories can achieve self-sustainment and long-term financial health while incorporating a proportion of impoverished patients who cannot afford out-of-pocket expenses.
Knowledge and attitudes of patients in underserved communities regarding antibiotic resistance, antibiotic stewardship, and pharmacist involvement in antibiotic prescribing: A regional survey
Authors: Nkemdirim Okere Arinze , Pinto Anthony Ryan , Suther Sandra
Published: November 2024

Purpose

Despite the effectiveness of antibiotic stewardship programs (ASPs) in improving antibiotic prescribing, these are rarely implemented in clinics serving underserved communities. Our objective was to understand patients’ perspectives on the factors that can impact implementation of ASPs and integration of pharmacists in antibiotic prescribing in rural clinics.

Methods

We conducted a survey using both quantitative questions and an open-ended question. To participate, patients had to receive care from a clinic serving low-income or rural communities and provide verbal consent to be included in the study. We analyzed the quantitative component of the data using descriptive statistics. The Pearson correlation coefficient was used to examine the relationship between respondents’ knowledge of the prevalence of antibiotic resistance and their attitudes toward ASPs and pharmacist integration in antibiotic prescribing.

Results

Of the 189 respondents who completed a survey, 51.3% were female and 51.3% were Caucasian. In our analysis, over 60% of patients reported knowing their prescribed antibiotics’ names, while less than 30% possessed adequate knowledge of the indication and duration of the prescribed antibiotics. There was a positive correlation between knowledge about antibiotic resistance and being comfortable involving pharmacists in antibiotic prescribing (P < 0.01).

Conclusion

Many patients supported pharmacist involvement in antibiotic prescribing. Understanding patients’ perceived attitudes will facilitate patient-centered, infrastructure-supported interventions by clinicians to improve antibiotic prescribing in the community.
A review of feature selection strategies utilizing graph data structures and Knowledge Graphs
Authors: Shao Sisi , Henrique Ribeiro Pedro , Ramirez Christina M , Moore Jason H
Published: November 2024

Feature selection in Knowledge Graphs (KGs) is increasingly utilized in diverse domains, including biomedical research, Natural Language Processing (NLP), and personalized recommendation systems. This paper delves into the methodologies for feature selection (FS) within KGs, emphasizing their roles in enhancing machine learning (ML) model efficacy, hypothesis generation, and interpretability. Through this comprehensive review, we aim to catalyze further innovation in FS for KGs, paving the way for more insightful, efficient, and interpretable analytical models across various domains. Our exploration reveals the critical importance of scalability, accuracy, and interpretability in FS techniques, advocating for the integration of domain knowledge to refine the selection process. We highlight the burgeoning potential of multi-objective optimization and interdisciplinary collaboration in advancing KG FS, underscoring the transformative impact of such methodologies on precision medicine, among other fields. The paper concludes by charting future directions, including the development of scalable, dynamic FS algorithms and the integration of explainable AI principles to foster transparency and trust in KG-driven models.
A multi-task prediction method based on neighborhood structure embedding and signed graph representation learning to infer the relationship between circRNA, miRNA, and cancer
Authors: Huang Lan , Wang Xin-Fei , Wang Yan , Guan Ren-Chu , Sheng Nan , Xie Xu-Ping , Wang Lei , Zhao Zi-qi
Published: November 2024

Motivation

Research shows that competing endogenous RNA is widely involved in gene regulation in cells, and identifying the association between circular RNA (circRNA), microRNA (miRNA), and cancer can provide new hope for disease diagnosis, treatment, and prognosis. However, affected by reductionism, previous studies regarded the prediction of circRNA-miRNA interaction, circRNA-cancer association, and miRNA-cancer association as separate studies. Currently, few models are capable of simultaneously predicting these three associations.

Results

Inspired by holism, we propose a multi-task prediction method based on neighborhood structure embedding and signed graph representation learning, CMCSG, to infer the relationship between circRNA, miRNA, and cancer. Our method aims to extract feature descriptors of all molecules from the circRNA-miRNA-cancer regulatory network using known types of association information to predict unknown types of molecular associations. Specifically, we first constructed the circRNA-miRNA-cancer association network (CMCN), which is constructed based on the experimentally verified biomedical entity regulatory network; next, we combine topological structure embedding methods to extract feature representations in CMCN from local and global perspectives, and use denoising autoencoder for enhancement; then, combined with balance theory and state theory, molecular features are extracted from the point of social relations through the propagation and aggregation of signed graph attention network; finally, the GBDT classifier is used to predict the association of molecules. The results show that CMCSG can effectively predict the relationship between circRNA, miRNA, and cancer. Additionally, the case studies also demonstrate that CMCSG is capable of accurately identifying biomarkers across various types of cancer. The data and source code can be found at https://github.com/1axin/CMCSG.
A multichannel graph neural network based on multisimilarity modality hypergraph contrastive learning for predicting unknown types of cancer biomarkers
Authors: Wang Xin-Fei , Huang Lan , Wang Yan , Guan Ren-Chu , You Zhu-Hong , Sheng Nan , Xie Xu-Ping , Yang Qi-Xing
Published: November 2024

Identifying potential cancer biomarkers is a key task in biomedical research, providing a promising avenue for the diagnosis and treatment of human tumors and cancers. In recent years, several machine learning–based RNA–disease association prediction techniques have emerged. However, they primarily focus on modeling relationships of a single type, overlooking the importance of gaining insights into molecular behaviors from a complete regulatory network perspective and discovering biomarkers of unknown types. Furthermore, effectively handling local and global topological structural information of nodes in biological molecular regulatory graphs remains a challenge to improving biomarker prediction performance. To address these limitations, we propose a multichannel graph neural network based on multisimilarity modality hypergraph contrastive learning (MML-MGNN) for predicting unknown types of cancer biomarkers. MML-MGNN leverages multisimilarity modality hypergraph contrastive learning to delve into local associations in the regulatory network, learning diverse insights into the topological structures of multiple types of similarities, and then globally modeling the multisimilarity modalities through a multichannel graph autoencoder. By combining representations obtained from local-level associations and global-level regulatory graphs, MML-MGNN can acquire molecular feature descriptors benefiting from multitype association properties and the complete regulatory network. Experimental results on predicting three different types of cancer biomarkers demonstrate the outstanding performance of MML-MGNN. Furthermore, a case study on gastric cancer underscores the outstanding ability of MML-MGNN to gain deeper insights into molecular mechanisms in regulatory networks and prominent potential in cancer biomarker prediction.
Advancing terrestrial ecology by improving cross-temporal research and collaboration
Authors: Azevedo-Schmidt Lauren , Landrum Madeleine , Spoth Meghan M , Brocchini Nikhil R , Hamley Kit M , Mereghetti Alessandro , Tirrell Andrea J , Gill Jacquelyn L
Published: November 2024

Ecology spans spatial and temporal scales and is inclusive of the history of life on Earth. However, research that occurs at millennial timescales or longer has historically been defined as paleoecology and has not always been well integrated with modern (neo-) ecology. This bifurcation has been previously highlighted, with calls for improved engagement among the subdisciplines, but their priority research areas have not been directly compared. To characterize the research agendas for terrestrial ecological research across different temporal scales, we compared two previous studies, Sutherland and colleagues (2013; neoecology) and Seddon and colleagues (2014; paleoecology), that outlined priority research questions. We identified several themes with potential for temporal integration and explored case studies that highlight cross-temporal collaboration. Finally, a path forward is outlined, focusing on education and training, research infrastructure, and collaboration. Our aim is to improve our understanding of biodiversity patterns and processes by promoting an inclusive and integrative approach that treats time as a foundational concept in ecology.
Automatic solar tracking system: a review pertaining to advancements and challenges in the current scenario
Authors: Paliyal Paramjeet Singh , Mondal Surajit , Layek Samar , Kuchhal Piyush , Pandey Jitendra Kumar
Published: November 2024

An automatic solar tracking system is an approach for optimizing the generation of solar power and modifying the angles and direction of a solar panel by considering changes in the position and path of the sun. The performance status of an automatic solar tracking system depends on various factors, including its design, location, and maintenance or repairs. The solar energy from the sun that the Earth intercepts is approximately 1.8 × 1011 MW, which is thousands of times greater than the intensity at which the Earth now uses all other commercially available energy sources combined. Currently, research into automatic solar trackers is on the rise, as solar energy is abundant in nature, but its use in a highly efficient way is still lacking. This paper provides a detailed literature review and highlights some key advancements and challenges associated with state-of-the-art automatic solar tracking systems. The performance of the dual-axis photovoltaic tracking system outperforms that of the stationary systems by more than 27% based on the overall system efficiency. Under diverse weather conditions, the efficiency of the scheduled-based solar tracking systems was enhanced by 4.2% compared with that of the light-dependent resistor-based solar trackers.