bluuebunny/crossref_metadata_2025 huggingface dataset:
Synthesis of a novel inorganic metal oxide-based composite 54(BaO.TiO2)-46(K2O.SiO2) via melt-quench technique: physical, structural, optical, and morphological properties for CO2 gas sensing applications
Authors: Mishra Rajat Kumar , Singh Ajeet , Avinashi Sarvesh Kumar , Shweta  , Kumari Savita , Fatima Zaireen , Hussain Ajaz , Yadav Bal Chandra , Gautam Chandkiram
Published: February 2025

Herein, a novel composite 54[BaO.TiO2]-46[K2O.SiO2], (BTKS) was synthesized via a melt-quenching approach for detection of CO2 gas. The measurements of CO2 gas sensing were performed in the range of 250–1500 ppm. XRD study reveals the polycrystalline nature of the composite with a major and minor phases of witherite (BaCO3), BaTiSi3O9 and BaTiO3. Further, UV-Visible spectroscopy was used and revealed the semiconducting nature of the composite. Further, SEM and TEM revealed rod-like morphology along with homogenous pores and voids within the composite, attributed for excellent sensing behaviour. FTIR and Raman spectroscopies were executed, revealing the bonds formation of Si–O–Si, Ti–O–Ti, and Si–O–Ti. The sensing response of the composite for CO2 gas at 1000 ppm was obtained 3.38 with response time 19.23s, and recovery time 21.54s respectively. The synthesized composite based portable, and cost-effective gas sensing device might be used for medical diagnostics to overcome health risks in the future.
Neural networks trained with SGD learn distributions of increasing complexity*
Authors: Refinetti Maria , Ingrosso Alessandro , Goldt Sebastian
Published: February 2025

The uncanny ability of over-parameterised neural networks to generalise well has been explained using various ‘simplicity biases’. These theories postulate that neural networks avoid overfitting by first fitting simple, linear classifiers before learning more complex, non-linear functions. Meanwhile, data structure is also recognised as a key ingredient for good generalisation, yet its role in simplicity bias is not yet understood. Here, we show that neural networks trained using stochastic gradient descent initially classify their inputs using lower-order input statistics, such as mean and covariance, and exploit higher-order statistics only later during training. We first demonstrate this distributional simplicity bias (DSB) in a solvable model of a single neuron trained on synthetic data. We then demonstrate DSB empirically in a range of deep convolutional networks and visual transformers trained on CIFAR10, and show that it even holds in networks pre-trained on ImageNet. We discuss the relation of DSB to other simplicity biases and consider its implications for the principle of Gaussian universality in learning.
Design of 64 V 24 Ah Battery Pack with Li-Ion 1865 Cells for Two-Wheels Electric Vehicle
Authors: Izzaturrahman A , Athallah R A N , Raharjo J
Published: February 2025

Electric vehicles have become increasingly popular in recent years, including in Indonesia. Many manufacturers are starting to produce their own versions of electric vehicles, including two-wheeled electric vehicles. Two-wheeled electric vehicles are known to be popular in Indonesia since it is used for running errands and other daily routines. As the popularity grows, the variety of battery packs are being produced and distributed. Battery packs variety is due to the lack of standardization in Indonesia. Therefore, this study aims to develop a battery with specifications of 64V and 24 Ah capacity. Test results show that the developed battery achieves a voltage of 69.67V when fully charged and a total capacity of 23.36 Ah. Dyno testing also demonstrates that the battery can generate power up to 1.54 HP with a maximum speed of 34 km/h. These specifications make the two-wheeled electric vehicles to be expected to travel further than others that are currently available in the market.
Design and Implementation of a Process Control System Using Bang-Bang Control and Polynomial Speed Acquisition for a Stirred Batch Reactor
Authors: Arifin  , Yulianti Lenni
Published: February 2025

This research focuses on designing and implementing a process control system with data acquisition for temperature regulation and agitator speed on a stirred batch reactor used for alpha-cellulose production through alkalization, a key step in the manufacture of Ball Powder Propellant (BPP). The temperature control system utilizes a bang-bang controller with a 2-degree Celsius hysteresis, ensuring stable operation with minimum overshoot. Concurrently, the agitator speed control system integrates an Arduino-based speed acquisition module to maintain an average RPM close to the setpoint, while exhibiting slight overshoot and accuracy deviation. The system includes a human-machine interface (HMI) developed in LabVIEW, which provides real-time monitoring and control, experimental results demonstrate effective process management is critical for consistent product quality in chemical reactor operations and a complete full system running with chemical substances already producing alfa cellulose is required for the next production step.
Enhanced Feature Matching in Image Stitching Using ORB for Image-Based Mapping Using UAV
Authors: Anoraga Muhammad Imron Catur , Ekawati Estiyanti , Mukhlish Faqihza
Published: February 2025

Image-based region mapping requires an image-stitching process to produce a complete map while preserving the details of the mapped objects. Image acquisition can be done using UAVs such as drones, and image stitching can be performed using the Oriented FAST and Rotated BRIEF (ORB) techniques. However, this algorithm has a drawback: There are many mismatches during feature matching. In this study, a maximum pixel displacement constraint between images was applied during the feature-matching process. Applying this constraint improved the feature-matching results due to a significant reduction of the mismatch rate from 84.28% to 25.17%. This reduction positively impacted subsequent stages, including map stitching. The mismatch removal process and the acquisition of transformation models during image registration became faster, reducing the processing time from 17m 36.8s to 1m 17.2s. Additionally, there was an improvement in the SSIM metric score, indicating that the stitched image results had a higher similarity to the reference image captured by a digital camera, increasing from 0.8423 to 0.8489.
Calibration of a Low-Cost Particulate Matter Sensor Using the Decay Method
Authors: Saputra Casmika , Faqiih Muhammad Nur , Thalia Asthari Fachsya , Safari Imel Aprilyana , Salam Rahmat Awaludin
Published: February 2025

Air pollution, particularly particulate matter (PM), poses significant health risks and environmental challenges. Real-time air quality monitoring is crucial for effective management and mitigation strategies, especially in personal exposure contexts. Wearable devices, commonly utilizing low-cost optical PM sensors, offer a promising solution. However, these low-cost sensors often require recalibration to ensure accuracy and reliability. This study focuses on calibrating the SPS30 particulate matter sensor, a popular optical sensor, to improve its performance for wearable applications. The calibration process was conducted using the decay method in an aerosol chamber, aligning the SPS30’s readings with those of a reference sensor (HT-9600). The results demonstrated an excellent correlation between the SPS30 and the reference sensor for both PM2.5 and PM10 measurements. This study confirms that proper calibration can enhance the SPS30’s accuracy, making it a reliable tool for real-time, personal air quality monitoring, which is essential for public health and environmental management.
Combining Coagulation and Filtration Methods for the Treatment of Laundry Wastewater
Authors: Habibah K A , Wibowo E , Ulya N , Rosi M , Sutisna
Published: February 2025

Laundry wastewater containing fabric softeners and detergents is hazardous to the environment and requires treatment before being discharged. The government’s wastewater quality criteria for laundry enterprises and activities are often exceeded by this wastewater due to its high levels of total dissolved solids (TDS), pH, and turbidity. In this study, two treatment methods—coagulation and filtration—were combined. Calcium oxide (CaO) was used as the coagulant in varying amounts (5, 10, 15, and 20 grams). The treated wastewater was then filtered through silica sand, activated carbon, and zeolite. The parameters analyzed were TDS, pH, and turbidity. Results showed that using 20 grams of CaO followed by filtration with zeolite media, was able to reduce turbidity by 99.94%, with the pH and TDS of the laundry waste reaching 8.79 and 1770, respectively. The use of CaO as a coagulant combined with zeolite as a filtration medium is the best combination for treating laundry waste to meet the government’s regulatory standards. Hence, combining coagulation and filtration using these two materials can serve as an affordable and effective method for laundry waste treatment. By implementing this method, the treated laundry waste becomes environmentally friendly.
In-situ study on fatigue failure of plain woven SiCf/SiC composites based on X-ray computed tomography
Authors: Ma P H , Hu D Y , Liu Y , Liu X , Wang Y , Wang R Q
Published: February 2025

SiCf/SiC ceramic matrix composites (CMCs) have emerged as key materials for thermal protection systems owing to their high strength-to-weight ratio, high-temperature durability, resistance to oxidation, and outstanding reliability. However, due to the complex microstructure of composites, including fibres, matrix, interfaces and manufacturing defects, the damage mechanisms of CMCs are extremely complex. In this study, in-situ X-ray computed tomography (CT) and scanning electron microscopy (SEM) were combined to investigate the damage mechanisms of plain woven SiCf/SiC composites under fatigue. The X-ray CT system, combined with an in-situ loading stage, allowed for the detailed characterization of internal damage evolution at different stages of fatigue, including changes in geometry morphology and defects. Meanwhile, SEM was used to observe the fracture surfaces of the material. Key results indicated that delamination damage occurs due to crack propagation in the matrix, which reduces the load-bearing area and leads to fibre fracture.
High dynamic magnetic transport system for substrate alignment
Authors: Denkena Berend , Klemme Heinrich , Zhang Jingcai
Published: February 2025

Optical waveguides can be manufactured using transfer processes. Therefore, the substrate needs to be transported and precisely aligned between different process steps. To achieve high productivity, a high dynamic transport system is necessary. However, for conventional transport systems, the dynamic positioning accuracy is limited due to friction of the contact-based guides. Thus, a friction-free transport system has the potential to achieve a higher dynamic positioning accuracy. In this paper a novel friction-free transport system with magnetic guide is presented. Its impressive load capacity and high dynamics have been verified through experiments. Based on the experimental data, the transport system is capable of providing loads of up to approximately 2000 N to meet printing requirements and a bandwidth of 75.0 Hz was achieved, which is 125% higher than the contact-based device.
Analysis of vibration due to combined misalignments in loaded spur gear systems
Authors: Tuiran R. , Ruge A. , Águila H. , Maury H.
Published: February 2025

This study investigates a single stage spur gear transmission system subjected to combined misalignments, such as parallel (radial and axial) and angular (yaw) misalignments, under varying load conditions. Two load levels were analysed: 0.1 Nm for "no load" and 1.2 Nm for "loaded" conditions. The input variables are combined misalignments and reaction loads, while the output variable is the vibration measurement taken at the bearing supports. These measurements were used to assess the effect of misalignment and load on the vibrational behaviour of the system. The test bench used for the experimental runs consists of a 2 hp motor and a hydraulic system that allows the reaction torques to be controlled. The results show that although the acceleration values vary under different load conditions, the overall trend remains consistent as long as no significant deformation occurs in the gears. Furthermore, the type of misalignment that most influences the variation in acceleration is yaw misalignment.
Design method for a hexapod curling robot with multiple tasks, multiple mechanism topologies, and multiple functions capabilities.
Authors: Xiao Y , Yin K , Chen X , Chen Z , Gao F
Published: February 2025

While current curling robots can perform the function of throwing the curling stone, their method of throwing differs significantly from that of human athletes. To better integrate robots into the sport of curling alongside athletes, they need to adopt a throwing technique similar to that of curlers. Consequently, the development of curling robots is confronted with the design challenges of multiple tasks, multiple mechanism topologies, and multiple functions capabilities. This paper proposes a four-step design method for legged robots to address this issue. First, the design requirements for the robot are determined by analyzing the curling stone throwing. Second, the robot's mechanism topology is established based on its functional needs. Then, the robot's configuration design is conducted based on the design requirements and mechanism topologies. Finally, the curling stone throwing for the robot is planned through task chains and behavior chains. Using this method, the design of a hexapod curling robot has been completed, and the robot's curling stone throwing function has been realized. The design method presented in this paper is also applicable to the development of other task-oriented legged robots, contributing to the advancement of legged robot applications.
Exercising Citizen’s Power: A Review of Social Movements Influencing Urban Forest Governance
Authors: Sylvia M. , Hasan M. M.
Published: February 2025

Amidst climate change challenges in urban areas, the interplay between development pressures and environmental sustainability intensifies. While cities integrate nature-based solutions like urban forests into planning, tensions arise when economic interests override environmental concerns, leading to the urban forest destruction for commercial development. Consequently, this discrepancy in priorities serves as a catalyst for social movements led by civic society, as citizens mobilize to advocate for the preservation and enhancement of urban forests. Thus, major civic society social movements are triggered when government decisions challenge the status quo, representing the last bastion of greenery in the community. This review investigates the motivations, organization, and communication strategies driving such movements and identifies the governance factors contributing to their success. By conducting an extensive literature review on citizen movements and employing a matrix-based comparative analysis of case studies from cities across Europe, Asia, and Latin America, we gained valuable insights into the dynamics of governance and citizen activism. From over 200 findings, 12 relevant case studies were meticulously selected to address these inquiries. Findings highlight those opaque governmental decisions, often disregarding public environmental concerns, are a key catalyst for mobilization, while climate crises serve as secondary motivators, reinforcing calls for transparent, participatory governance. Ultimately, this study contributed to the discourse on urban forest governance by elucidating the complex dynamics of citizen-led initiatives and offering pathways for enhancing citizen participation in decision-making processes towards co-governance of urban forests.
Biodiversity and Carbon Stocks of Mangrove Forests in Nusantara Capital City of Indonesia
Authors: Kiswanto  , Mardiany  , Jansi Budiawan Tekko , Farahdita Wanda Laras , Ola Rosa Penaten , Bola Stevanus Dolin , Diana Rita
Published: February 2025

Degradation and conversion of mangrove forests, recognized as blue carbon ecosystems, have predominantly impacted Indonesia. The Indonesian government’s pronouncement to transfer the capital from Jakarta to Nusantara in East Kalimantan Province raises the possibility of causing ecosystem damage to mangrove forests during infrastructure reconstruction. The study pointed to identify the various species and calculate the total of carbon stocks in mangroves due to replacement of the Nusantara Capital City. This study will collect data using two 125-meter transect lines, each with three circular plots. The survey found several mangrove species, namely Rhizophora apiculata, R. mucronata, Sonneratia alba, Xylocarpus granatum, and Ceriops tagal. R. apiculata consistently has the maximum values of Importance Value Index (IVI), including seedlings, saplings, and trees. According to the findings, mangrove stands have a carbon dioxide storage capacity of 156.563 tonnes per hectare and a total biomass of 333.113 tonnes per hectare. This study proposes suggestions for preserving and restoring mangrove forest systems by using the smart forest city idea in Nusantara Capital City.
Species Diversity and Carbon Storage of Tanah Grogot Urban Forest in Paser Regency of East Kalimantan
Authors: Marjenah  , Ramadani  , Farahdita Wanda Laras , Kiswanto
Published: February 2025

Urban development has a negative impact on environmental quality and contributes to increased carbon emissions. Green open spaces, like urban forests, are essential for maintaining a harmonious balance between development and the environment. The study focuses on evaluating the Tanah Grogot Urban Forest’s species composition and carbon stock. Carbon stocks are calculated using a census tree inventory that covers an area of 0.85 hectares and measures the diameter and height of the trees. The study found that Samanea saman and Terminalia catappa have the maximum Important Value Index (IVI) scores between all types. These urban forests have moderately of species diversity, according to the Shannon Index (H’). Samanea saman, Terminalia catappa, and Tectona grandis were the trees with the greatest ability to store carbon. These tree species were widely distributed and had extensive tree diameters. Enrichment planting is needed in urban landscapes to enhance species diversity and increase carbon storage.
The Mammals of Indonesia’s New Capital: Baseline Mammalian Data for Forest City Management and Wildlife Monitoring
Authors: Rustam  , Matius Paulus , Boer Chandradewana , Sardjono Mustofa Agung , Syoim Mochamad , Ariyanto  , Prasetya Arie , Fredriksson Gabriella , Nuryani Ahmad , Nainggolan Kristina , Landon Nigel
Published: February 2025

The “forest city” concept prioritizes green area management in the new Indonesian capital (IKN) of Nusantara, with key aspects including the protection of forested areas, restoration of deforestation and degradation areas, and monitoring of wildlife species. This study aimed to identify existing mammalian fauna in the IKN by direct and in-direct observation. Line transects were used for direct observation, and camera traps, cage traps, harp traps, mist nets, and documented animal sign were used for in-direct observation. Focal survey areas for this study included old and young secondary forests and forest plantations found in the area delineated for IKN. These sites included the Grand Forest Park of Bukit Soeharto, Bukit Bangkirai, and areas inside the PT Inhutani and PT ITCI Hutani Manunggal concessions within Mentawir village and the Gunung Parung region. Across these sites, from 2020-2023 a regular survey was conducted at 74 points in 9 focal areas to update and clarify historical mammalian data. The results showed that natural forested areas are very important for mammalian fauna, especially in old secondary forest. We found 52 species of mammal, including seven species of primates (e.g., Maroon Langur (Presbytis rubicunda), Proboscis monkey (Nasalis larvatus), Bornean Gibbon (Hylobates muelleri), Slow Loris (Nycticebus coucang)), four species of wild cats (e.g., Clouded leopard (Neofelis diardi), Marbled Cat (Pardofelis marmorata)), and five species of ungulates (e.g. Sambar (Rusa unicolor), Bornean Yellow Muctjac (Muntiacus atherodes)). There are many species that depend on forests in the IKN that need to be protected, and live monitoring using technologies, such as simple 4G camera traps, GPS collars, and bioacoustics recorders will be very helpful for forest protection, wildlife management, and minimizing human-wildlife conflict during IKN development.
Potential for developing Porang (Amorphopallus oncophyllus Prain) in logged over area forest TPTI system as a buffer area for IKN East Kalimantan Province
Authors: Kasransyah  , Marjenah  , Rujehan  , Karyati  , Ruslim Y , Matius P , Syahrinuddin  , Soetioso R , Maulidah N I
Published: February 2025

The tropical rainforest landscape in East Kalimantan province has proven to be a pivotal driver of the regional and national economy. Spanning 6,055,793 hectares of production forest, a majority of which is under the management of 106 active forest utilization permit holders (PBPH), the region employs the Indonesian Planting Select Logging (TPTI) silviculture system to manage and enhance the value of logged over forest areas. This experiment aims to determine the growth rate of Porang plants in logged over areas forest under the TPTI system using a complete randomized design with six replicates and three treatment levels: without organic fertilizer/control (P0), application of 1000g/plant manure (P1), and biochar + 1000g/plant manure (P2). The data obtained were then subjected to ANOVA test. The test results revealed that the application of biochar + manure 1000g/plant (P2) significantly influenced average growth rate the plant height of 11.34 cm/month, Leave number of 6.17 sheet/month, and fresh tuber yield of 58.7 g. Whereas the control treatment only gave average results plant height of 9.09 cm/month, Leave number of 4.83 sheet/month, and fresh tuber yield of 22.2 g. These findings underscore the potential of Porang as a viable interstitial crop within production forest lands, emphasizing the feasibility of integrating it into agroforestry systems.
A review: investigation of post-mining treatment in coal production especially in East Kalimantan
Authors: Indrawan Wisnu , Andini Ulfa Niki , Yulia Fayza , Wahyono Yoyon , Rasjidin Roesfiansjah
Published: February 2025

This study examines the post-mining treatment in coal production, with a particular emphasis on East Kalimantan. Mining activities have a substantial economic impact; however, they can also have detrimental effects on the environment and the communities in the vicinity if mining detritus is not properly managed. This study emphasises the utilisation of contemporary technology to monitor and mitigate coal dust contamination, as well as a variety of post-mining land management strategies, including reclamation, restoration, and rehabilitation. This study also examines the implementation of the “Water-Energy-Emission Nexus” (WEEN) model, which optimises the correlation between water consumption, energy consumption, and contaminant emissions in coal-fired power plants. Although the WEEN model has the potential to decrease emissions by up to 72%, the results indicate that this reduction is accompanied by a 17% increase in energy and water consumption. In order to achieve optimal mining results with minimal environmental impacts, it is imperative to strictly enforce regulations and involve local stakeholders. This research suggests that additional research be conducted to develop sustainable solutions and advocates for the implementation of advanced technology to mitigate pollution.
Enhancing Environmental Sustainability and Socio-Economic Prosperity: The Feasibility of the AMIS Methodology in Mitigating H2S Impacts in Ulumbu Geothermal Working Area
Authors: Ahmad D.M , Akhlaqul D.
Published: February 2025

Geothermal energy is one of Indonesia’s national strategic programs to reduce the country’s dependence on fossil fuels. Geothermal energy also plays an important role in improving the economic conditions of communities in the surrounding area. However, this economic growth has also been accompanied by negative impacts on the environment. The dispersion of hydrogen sulfide (H2S) gas has been a major concern in the Ulumbu Geothermal Working Area (WKP), Manggarai Regency, East Nusa Tenggara (NTT) since it developed in 2012. This research aims to explore the feasibility of AMIS (Abbattimento Mercurio ed Idrogeno Solforato) methodology to mitigate the impact of H2S. The research also emphasizes the importance of careful planning by project developers and local government to achieve a balanced approach between methodological advancement and environmental preparedness. By combining methodological refinement with careful planning, this study highlights the good potential of the AMIS methodology in mitigating H2S impacts. This convergence of approaches not only promotes environmental sustainability but also revitalizes agricultural and plantation activities and advances the socio-economic welfare of the Ulumbu area community.
Pressure Prediction in Two-Phase Geothermal Well Flow Using Physics Informed Neural Network (PINN)
Authors: Aji Nugroho Agung , Sutopo  , Ashat Ali
Published: February 2025

To ensure optimal production from geothermal wells, it is essential to simulate fluid behavior accurately in the reservoir and wellbore. Wellbore simulation uses mathematical models to predict the pressure drop in fluid flow from the bottom hole to the wellhead. However, it is essential to understand that using numerical simulators still has limitations due to inappropriate empirical equations and unrealistic assumptions. Artificial Neural Network (ANN) can learn the correlation between input (wellbore geometry, temperature, pressure, and mass flow rate) and output variables (pressure drop) well. ANN is very promising for solving problems in the field of science that involve processes that are not fully understood or that require complex computational processes. However, the application of ANN in the science domain has limitations because it requires extensive data, the inability to produce physically consistent predictions, and the lack of generalization to scenarios outside the training data. Physics-Informed Neural Network (PINN) integrates ANN and scientific knowledge to overcome inconsistent physical parameters with training data that is not fully representative. We will discuss the physics loss function used to produce the PINN model with the best wellbore simulation. Overall, the PINN model with physics loss functions corrected by temperature can provide more accurate pressure predictions in the wellbore and fewer errors than the ANN model. The total error produced by the PINN model for five wells is MAE 2.780 and RSME 3.151. However, the PINN model that has been developed is not suitable for use in the one-phase water zone.
What's Wrong with Stereotyping?
Authors: Beeghly Erin
Published: February 2025

What’s Wrong with Stereotyping? offers a groundbreaking, accessibly written philosophical account of the ethics of stereotyping. The book advances a complex and often surprising notion of what stereotyping is, and when and why it is wrongful. Using philosophy, law, psychology, and history, as well as thought-provoking examples and models for social change drawn from the lived experiences of marginalized groups, the book emphasizes the messiness of moral reality and the importance of looking to the past to understand the ethical perils of social generalizing. Readers come away with a radically pluralistic, open-ended understanding of stereotyping that they can use to identify wrongful stereotyping in their own lives and our contemporary world.
Introduction
Authors: Beeghly Erin
Published: February 2025

This introduction familiarizes readers with the idea of an explanatory project in ethics and, in doing so, invites them to contemplate the ethical puzzles associated with stereotyping. Is stereotyping always morally wrong, as people often believe? Is it only sometimes wrong? What explains why it is wrong when it indeed is? This is the puzzle of stereotyping. Moving chapter by chapter, this introduction sketches the overall shape of book’s argument so that readers can better orient themselves as they read, explains its down-to-earth methodology, and previews the radically pluralistic theory of wrongful stereotyping for which it argues.
A Starting Point for Theorizing
Authors: Beeghly Erin
Published: February 2025

This chapter examines stereotypes and stereotyping from linguistic, psychological, and sociological perspectives. Investigating the psychology of stereotypes and stereotyping, it examines their connection to generalization and induction, core aspects of human rationality. Building on the work of Patricia Hill Collins, it also contends that cultural stereotypes take the form of “controlling” ideas and images. To capture stereotyping in all its manifestations and emphasize their interconnection, the chapter introduces morally neutral definitions that don’t build wrongness into the very idea of what it means to stereotype. To stereotype a group, it says, is to characterize that group as a collective entity. To stereotype an individual is to judge that person by group membership. These definitions don’t sweep power relations under the rug. Rather, they recognize that wrongful stereotyping involves the social hijacking of generalizing tendencies that are not inherently immoral and which in fact are essential to human functioning.
Prejudice and the Problem of Statistical Stereotyping
Authors: Beeghly Erin
Published: February 2025

This chapter explores prejudice-focused objections to stereotyping in the testimonies of American AIDS activists in the 1980s and 1990s. It begins with classic prejudicial stereotyping, a flagrant form of wrongful stereotyping that involves false morally vicious attitudes. I then examine a putative limitation of prejudice-focused critiques. Not all discriminators—and not all people who stereotype—have vicious attitudes. Statistical stereotyping is a case in point. Exploring a realistic example of medical statistical stereotyping critiqued by feminist AIDS activists, the chapter highlights the philosophical limits of prejudice-focused critiques. At the same time, it contends that any theory of wrongful stereotyping that ignores prejudice will be both incomplete and misleading. Though prejudice may not always explain what’s morally wrong with stereotyping, it sometimes does, revealing a distinctive way in which acts of stereotyping can wrong individuals, and the groups to which they belong, by disrespecting them.
Gesture
Authors: Gawne Lauren
Published: February 2025

The gestures that we use when we speak are an important, if often overlooked, part of how we communicate. This book provides a friendly, fast-paced introduction to the field of Gesture Studies. Gestures are those communicative actions made with the human body that accompany spoken or signed language. Paying attention to gesture means paying attention to the fuller context in which humans communicate. Gesture is absolute, in that every human community that has language also has gestures as part of that language. But gesture is also relative, in that it is far more heavily context dependent than other elements of communication. This book provides a broad introduction to current understandings of the nature and function of gesture as a feature of communication. This Slim Guide covers the ways gesture works alongside speech and the different categories of gesture. The way these categories are used varies across cultures and languages, and even across specific interactions. We acquire gesture as part of language, and it is deeply entwined with language in the brain. Gesture has an important role in the origin of language, and in shaping the future of human communication. The study of gesture makes a crucial interdisciplinary contribution to our understanding of human communication. This Slim Guide provides an introduction to Gesture Studies for readers of all backgrounds.
Discovery and Phase 1 study of a novel monoclonal antibody against human IL-1β for the treatment of IL-1β-mediated diseases
Authors: Cho Minseon , Tam Susan H , Shi Lihua , Fung Isa , Tornetta Mark , Canziani Gabriela A , Fung Man-Cheong , Chiu Mark L , Han Chao , Zhang Di
Published: February 2025

Interleukin-1β (IL-1β) is a key mediator of innate immunity against pathogen infections. However, dysregulated IL-1β activity is associated with various autoinflammatory, autoimmune, degenerative, atherosclerotic diseases, and cancers. Biologic drugs that neutralize excess IL-1β activity, such as canakinumab, have been effective in treating IL-1β-mediated diseases. This article reports the discovery and development of a novel humanized anti-IL-1β antibody, designated as TAVO103A, which exhibited potent binding affinities to human and monkey IL-1β. TAVO103A demonstrated more potent neutralization of IL-1β activities compared to canakinumab in multiple assays, including tests on the IL-1β-driven signal transduction cascade, inflammatory cytokine release from MRC-5 cells, chemokine release from A549 cells, and the proliferation of D10.G4.1 helper T cells. Ex vivo studies showed that TAVO103A effectively neutralized IL-1β-mediated release of pro-inflammatory cytokines from peripheral blood mononuclear cells (PBMC). In addition, TAVO103A exhibited dose-dependent efficacy in a knee joint inflammation mouse model. TAVO103A underwent Fc engineering to reduce binding to Fcγ receptors, increase affinity to FcRn receptors, and enhance its resistance to proteolytic degradation. In a Phase 1 study, TAVO103A was found to be safe, well tolerated, and demonstrated a median half-life of 63 days in healthy subjects. By recognizing a different epitope, TAVO103A provided more potent neutralization of IL-1β activities, a longer circulating half-life, and improved safety profiles compared to canakinumab, positioning it to be a potential best-in-class therapeutic option for various IL-1β-mediated diseases.
A case report of cardiogenic shock due to tachycardic atrial fibrillation: a life-saving catheter ablation for atrial fibrillation and prone position during veno-arterial extracorporeal membrane oxygenation
Authors: Wakita Masaki , Hosokawa Yusuke , Ishihara Shiro , Maruyama Mitsunori , Asai Kuniya
Published: February 2025

Background

Veno-arterial extracorporeal membrane oxygenation (VA-ECMO) is vital for acute cardio-respiratory failure, but challenges persist sometimes in weaning. Prone positioning, beneficial in veno-venous extracorporeal oxygenation (VV-ECMO), is generally avoided in VA-ECMO patients because of the risks such as bleeding from the catheter insertion site and dislodging of the perfusion cannula or tracheal tube.

Case Summary

A 71-year-old male with paroxysmal atrial fibrillation (AF) presented with dyspnea. Chest computed tomography (CT) and echocardiogram revealed severe pneumonia and decreased cardiac function (left ventricular ejection fraction (LVEF) 20%). The patient was diagnosed with heart failure complicated by severe pneumonia. Despite treatment, respiratory and circulatory status deteriorated, necessitating a VA-ECMO. Chest CT showed collapsed lungs, especially on the dorsal side. Thus, prone positioning was initiated under VA-ECMO with attention to potential complications associated with the postural change. Then, his respiratory status was improved dramatically. However, the hemodynamic status could not be probably because of tachycardic AF. Electrical cardioversions failed to maintain sinus rhythm and heart rate was not adequately controlled. We decided to perform radiofrequency catheter ablation (RFCA) of tachycardic AF under VA-ECMO. Pulmonary vein isolation and conduction block line in the cavo-tricuspid isthmus were made, and converted to sinus rhythm, enabling weaning of VA-ECMO. The primary cause of the hart failure was considered to be tachycardia-induced cardiomyopathy, as the LVEF improved to 55%.

Discussion

RFCA for AF can be effective even in case of cardio-respiratory failure necessitating VA-ECMO. Furthermore, prone positioning can be performed not only in VV-ECMO but also in VA-ECMO.
Experimental evolution reveals trade-offs between sexual selection and heat tolerance in Drosophila prolongata
Authors: De Nardo Alessio N , Meena Abhishek , Maggu Komal , Eggs Benjamin , Sbilordo Sonja H , Lüpold Stefan
Published: February 2025

Sexual selection promotes traits that enhance mating or fertilization success, but these traits can be very costly under harsh environmental conditions. The extent to which differential investment in costly traits under varying intensities of sexual selection is related to their susceptibility to environmental stress remains unclear. This study explored how experimental evolution under different operational sex ratios (OSRs) shapes traits and reproductive success of male Drosophila prolongata, and how developmental and/or adult heat stress affect the expression of these traits. We found males from even and slightly male-biased OSRs to be larger and display greater reduction in body size under developmental heat stress, suggesting pre-mating sexual selection on body size and condition-dependent thermal sensitivity. These populations also exhibited consistently high mating and fertilization success across temperatures, potentially indicating selection for robust phenotypes with ‘good genes’ that perform well regardless of temperature. Conversely, males from strongly male-biased OSR populations experienced more pronounced decline in sperm competitiveness following exposure to developmental or adult heat stress. These results highlight how environmental stressors differentially impact populations, shaped by varying strengths of pre- and post-mating sexual selection. These observed patterns suggest potential interactions between past selection and the ability to adapt to changing environments.
The nasal microbiota of two marine fish species: diversity, community structure, variability and first insights into the impacts of climate change-related stressors
Authors: Cohen-Rengifo Mishal , Noel Cyril , Ytteborg Elisabeth , Bégout Marie-Laure , Lazado Carlo C , Le Blay Gwenaelle , Hervio-Heath Dominique
Published: February 2025

Vertebrate nasal microbiota (NM) plays a key role regulating host olfaction, immunity, neuronal differentiation, and structuring the epithelium. However, little is known in fish. This study provides the first comprehensive analysis of the NM in two marine fish species, the European seabass and the Atlantic cod. Given its direct environmental exposure, fish NM is likely influenced by seawater fluctuations. We analysed the community structure, specificity regarding seawater, and interindividual variability of 32 to 38 fish reared under ambient conditions. Additionally, we conducted an experiment to investigate the influence of acidification and a simplified heatwave on cod NM (3 fish per replicate). High-throughput 16S rRNA sequencing revealed species-specific NM communities at the genus-level with Stenotrophomonas and Ralstonia dominating seabass and cod NM, respectively. This suggests potential habitat- or physiology-related adaptations. The most abundant bacterial genera in seabass NM were also present in seawater, suggesting environmental acquisition. Alpha diversity was highest in Brest seabass NM and variability greatest in Tromsø cod NM. Simulated climate change-related scenarios did not significantly alter cod NM structure. We propose a minimum of 13 cod rosettes per replicate for future studies. This research establishes a foundation for understanding marine fish NM and its response to environmental changes.
Tea polyphenol mediated CsMYB77 regulation of CsPOD44 to promote tea plant (Camellia sinensis) root drought resistance
Authors: Xu Rong , Shao Chenyu , Luo Yuqi , Zhou Biao , Zhu Qian , Qiu Shuqi , Liu Zhonghua , Liu Shuoqian , Shen Chengwen
Published: February 2025

Drought stress significantly alters the metabolic homeostasis of tea plants; however, few studies have examined the role of specific metabolites, particularly tea polyphenols, in drought resistance. This study reveals that the tea polyphenol content in drought-tolerant tea cultivars tends to increase under drought conditions. Notably, in environments characterized by staged and repeated drought, changes in tea polyphenol are significantly positively correlated with drought resistance. To investigate this further, we irrigated the roots with exogenous tea polyphenols before subjecting the plants to drought. Our findings indicated that the absorptive roots of the experimental group exhibited enhanced development, improved cellular integrity, and a significant increase in peroxidase activity. A comprehensive analysis of the transcriptome and metabolome revealed that tea polyphenols are closely associated with the phenylpropanoid metabolism pathway. Notably, CsMYB77 and CsPOD44 genes were identified as highly correlated with this pathway. Overexpression experiments in Arabidopsis thaliana demonstrated that CsMYB77 promotes the expression of phenylpropanoid pathway genes, thereby enhancing drought resistance. Conversely, antisense oligonucleotide silencing of CsMYB77 decreased drought resistance in tea plants. Additional experiments, including yeast one-hybrid assays, luciferase complementation imaging, dual-luciferase assays, and electrophoretic mobility shift assays, confirmed that CsMYB77 positively regulates the expression of CsPOD44. In summary, our findings indicate that the differences in drought tolerance among tea cultivars are closely linked to phenylpropanoid metabolism. Specifically, tea polyphenols may mediate the regulatory network involving CsMYB77 and CsPOD44, thereby enhancing stress resistance by promoting root development. This study offers new insights into the breeding of drought-resistant tea cultivars.
Aggregatin is a mitochondrial regulator of MAVS activation to drive innate immunity
Authors: Gao Ju , Ding Mao , Xiyang Yanbin , Qin Siyue , Shukla Devanshi , Xu Jiawei , Miyagi Masaru , Fujioka Hisashi , Liang Jingjing , Wang Xinglong
Published: February 2025

Mitochondrial antiviral-signaling protein (MAVS) is a key adapter protein required for inducing type I interferons (IFN-Is) and other antiviral effector molecules. The formation of MAVS aggregates on mitochondria is essential for its activation; however, the regulatory mitochondrial factor that mediates the aggregation process is unknown. Our recent work has identified the protein Aggregatin as a critical seeding factor for β-amyloid peptide aggregation. Here we show that Aggregatin serves as a cross-seed for MAVS aggregates on mitochondria to orchestrate innate immune signaling. Aggregatin is primarily localized to mitochondria in the cytosol and has the ability to induce MAVS aggregation and MAVS-dependent IFN-I responses alone in both HEK293 cells and human leukemia monocytic THP-1 cells. Mitochondrial Aggregatin level increases upon viral infection. Also, Aggregatin knockout suppresses viral infection-induced MAVS aggregation and IFN-I signal cascade activation. Nemo-like kinase is further identified as a kinase phosphorylating Aggregatin at Ser59 to regulate its stability and cross-seeding activity. Collectively, our finding reveals an important physiological function of Aggregatin in innate immunity by cross-seeding MAVS aggregation.
Targeting PGE2 mediated senescent neuron improves tumour therapy
Authors: Zhao Jianyi , Wu Linshi , Cai Gang , Ou Dan , Liao Keman , Yang Jian , Zhou Li , Huang Renhua , Lin Shukai , Huang Xi , Lv Qi , Chen Juxiang , Cao Lu , Chen Jiayi , Lin Yingying
Published: February 2025

Background

Recent studies have highlighted bidirectional signalling between tumours and neurons; however, the interactions between tumours and neurons in response to radio-/chemotherapy remain obscure, which hampers the tumour treatment.

Methods

Glioblastoma organoids (GBOs) and primary neuron coculture, targeted metabonomics, RNA pulldown, mass spectrum, co-immunoprecipitation, RNA-sequencing, transcript/protein validations and multi-electrode arrays were performed to analyse neuron-tumour interaction in response to therapy. In vivo validations were conducted in orthotopic mouse models. Diagnostic and prognostic values were evaluated in serum, tissue-microarray as well as TCGA.

Results

GBOs recruited and induced pro-tumour-survival senescent neurons upon radiation/chemotherapeutic treatment. Targeted metabonomics revealed that significantly increased tumour-derived prostaglandin E2 (PGE2) induced neuronal senescence phenotype. Screening of enzymes involved in PGE2 synthesis identified prostaglandin E synthase 3 (PTGES3) as the key enzyme responsible for PGE2 upregulation. Biochemical studies revealed that irradiation or chemotherapeutic drug-triggered asparagine endopeptidase (AEP) specifically cleaved eIF4A1 to produce teIF4A1-C, which dissociated from DDX6 and recruited eIF4A3 and PABPN1 to promote the mRNA stability of PTGES3. Elevated PGE2 reciprocally enhanced AEP expression. Inhibiting PGE2 or AEP reduced neuronal senescence and delayed tumour progression. Strikingly, single-cell analysis further showed that expressions of AEP/PTGES3/EIF4A1 in tumour cells were consistent with senescent neuronal CDKN1A in high-neuronal-connectivity glioblastoma. The serum PGE2 concentration was elevated after radiation and higher in resistant glioblastoma patients. High expression of PTGES3 was associated with a poor prognosis.

Conclusions

Our study revealed that the AEP/PGE2 feedback loop modulates tumour-induced neuronal senescence upon radio-/chemotherapy and highlight the therapeutic value to improve tumour therapy.
Differentiating between renal medullary and clear cell renal carcinoma with a machine learning radiomics approach
Authors: Jiwani Rahim , Pal Koustav , Paolucci Iwan , Odisio Bruno , Brock Kristy , Tannir Nizar M , Shapiro Daniel D , Msaouel Pavlos , Sheth Rahul A
Published: February 2025

Background

The objective of this study was to develop and validate a radiomics-based machine learning (ML) model to differentiate between renal medullary carcinoma (RMC) and clear cell renal carcinoma (ccRCC).

Methods

This retrospective Institutional Review Board -approved study analyzed CT images and clinical data from patients with RMC (n = 87) and ccRCC (n = 93). Patients without contrast-enhanced CT scans obtained before nephrectomy were excluded. A standard volumetric software package (MIM 7.1.4, MIM Software Inc.) was used for contouring, after which 949 radiomics features were extracted with PyRadiomics 3.1.0. Radiomics analysis was then performed with RadAR for differential radiomics analysis. ML was then performed with extreme gradient boosting (XGBoost 2.0.3) to differentiate between RMC and ccRCC. Three separate ML models were created to differentiate between ccRCC and RMC. These models were based on clinical demographics, radiomics, and radiomics incorporating hemoglobin electrophoresis for sickle cell trait, respectively.

Results

Performance metrics for the 3 developed ML models were as follows: demographic factors only (AUC = 0.777), calibrated radiomics (AUC = 0.915), and calibrated radiomics with sickle cell trait incorporated (AUC = 1.0). The top 4 ranked features from differential radiomic analysis, ranked by their importance, were run entropy (preprocessing filter = original, AUC = 0.67), dependence entropy (preprocessing filter = wavelet, AUC = 0.67), zone entropy (preprocessing filter = original, AUC = 0.67), and dependence entropy (preprocessing filter = original, AUC = 0.66).

Conclusion

A radiomics-based machine learning model effectively differentiates between ccRCC and RMC. This tool can facilitate the radiologist’s ability to suspicion and decrease the misdiagnosis rate of RMC.