bluuebunny/crossref_metadata_2025 huggingface dataset:
Bearing Capacity of a Concrete Grouting Pad on the Working Surface of a Highway Tunnel Shaft
Authors: Fang Tengfei , Zhao Zongzhi , Chen Jianxun , Luo Yanbin , Liu Weiwei , Li Dong , Yu Ruibin , Li Jian
Published: March 2024

A grouting pad is the key structure for the construction of water inrush grouting on the shaft working surface. Previous methods of calculating the bearing capacity have limitations due to a lack of understanding of the failure mode. To investigate the bearing capacity of a concrete grouting pad on the working surface of a shaft, this paper establishes a mechanical model for the punching shear failure of a grouting pad under symmetrical loading conditions. A unified solution for the bearing capacity is derived, and the influence of parameters is discussed. In addition, a new method for designing the plastic limit thickness is proposed based on this research. The results show that the reason for the grouting pads’ punching shear failure resulted from the formation of peripheral grouting holes “weak ring” caused by the reduction of the bearing capacity. When the thickness of B0 remains constant, the bearing capacity qu of the grouting pad is inversely proportional to the ratio of the diameter and the area of the bottom load. Therefore, following the method of “dividing, interval, and jumping holes” during grouting construction is recommended. The greater the thickness of the grouting pad, the greater the bearing capacity qu will be. When the grouting pad diameter is 2r2 and the thickness B0 is constant, the bearing capacity qu increases with the material tensile strength ft. When designing grouting pads, following the principles of “large thickness, uniform strength theory, high strength materials” will improve bearing performance. The findings have been implemented in the design of the grouting pad thickness for the Tianshan Shengli Tunnel shaft project, which can successfully solve the problem of frequent cracking caused by the weak bearing capacity of a grouting pad. The findings can provide a theoretical basis and reference for the design and construction of grouting pads in a highway tunnel shaft.
Green Solvent Extraction of Antioxidants from Herbs and Agro-Food Wastes: Optimization and Capacity Determination
Authors: Hamieau Malo , Loulergue Patrick , Szydłowska-Czerniak Aleksandra
Published: March 2024

Herbs and agro-food wastes are rich sources of bioactive compounds vital for organisms and valuable for many fields of industry. Therefore, in this study, green deep eutectic solvents (DESs) such as choline chloride/citric acid (ChCl:CitA), glucose/citric acid (Gu:CitA), glucose/urea (Gu:U), betaine/citric acid (B:CitA), and betaine/urea (B:U) at a molar ratio of 1:1 for ultrasound-assisted extraction (UAE) of antioxidants from four herbs (chamomile—Cha, lemon balm—LB, mint—M, and nettle—N) and two agro-food wastes (buckwheat husk—BH and chokeberry pomace—ChoP) were proposed. The antioxidant capacity (AC) of the obtained extracts was evaluated utilizing three antioxidant assays: cupric reducing antioxidant capacity (CUPRAC = 0.0–429.9 μmol of Trolox (TE)/g); 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS = 0.0–146.5 μmol TE/g); and 2,2-diphenyl-1-picrylhydrazyl (DPPH = 11.9–170.3 μmol TE/g). The LB extracts revealed the highest CUPRAC (59.3–429.9 μmol TE/g), ABTS (30.7–144.3 μmol TE/g), and DPPH (32.6–170.3 μmol TE/g) values. Due to the lowest antioxidant potential of LB extracts prepared using ChCl:CitA (AC = 30.7–59.3 μmol TE/g) and the highest AC demonstrated by extracts based on B:U (AC = 144.3–429.9 μmol TE/g), the UAE conditions using a new DES consisting of ChCl and U were optimized by the Box–Behnken design (BBD). Effects of three independent variables, molar ratios of the ChCl and U (mol/mol), water content (%), and sonication time (t) on the AC of LB extracts were studied by response surface methodology (RSM). The results of principal component analysis (PCA) and hierarchical cluster analysis (HCA) demonstrated that different DESs had great differences in the extraction of antioxidant compounds from herbs and agro-food residues.
Yarn Angle Detection of Glass Fiber Plain Weave Fabric Based on Machine Vision
Authors: Hou Jiatong , Wang Tao , Xu Jiazhong , Cao Moran
Published: March 2024

To address the issue of low accuracy in the yarn angle detection of glass fiber plain weave fabrics, which significantly impacts the quality and performance of the final products, a machine vision-based method for the yarn angle detection of glass fiber fabrics is proposed. The method involves pre-processing the image with brightness calculation, threshold segmentation, and skeleton extraction to identify the feature region. Line segment detection is then performed on this region, using the Hough transform. The concept of a “line segment evaluation index” is introduced, and it was used as a criterion for assessing the quality and relevance of detected line segments. Moreover, the warp and weft yarn extrusion area contours refer to the reconstructed outlines of yarn areas, achieved by combining the center of mass extraction with morphological operations and used to accurately determine the yarn angle. Tested under a range of challenging scenarios, including varied lighting conditions, fabric densities, and levels of image noise, this method has demonstrated robust stability and maintained high accuracy. These tests mimic real-world manufacturing environments, where factors such as ambient light changes and material inconsistencies can affect the quality of image capture and analysis. The proposed method has high accuracy, as shown by MSE and a Pearson’s r of 0.931. By successfully navigating these complexities, the proposed machine vision-based approach offers a significant enhancement in the precision of yarn angle detection for glass fiber fabric manufacturing, thus ensuring improved quality and performance of the final products.
Enhanced YOLO- and Wearable-Based Inspection System for Automotive Wire Harness Assembly
Authors: Li Shuo , Yuan Mingzhe , Wang Wenhong , Cao Feidao , Shi Hongyan , Zhang Yuhang , Meng Xiangpu
Published: March 2024

In response to the challenges associated with the misassembly, omission, and low manual inspection efficiency in automobile wiring harness relay assemblies, a novel online detection system has been engineered. This system consists of a mobile-based visual imaging system and an improved YOLOv5-based detection algorithm that tracks human movement to acquire images and videos. The system is coupled with deep learning for real-time detection and recognition for error-proofing the installation process of automotive wiring harness relays. This innovation aims to facilitate error-proof inspection during the assembly process of automotive wiring harness relays. The YOLOv5s model is augmented with an Adaptive Spatial Feature Fusion (ASFF) module, enhancing multi-scale feature integration capabilities. A Global Context Network (GCNet) is incorporated into the C3 module to emphasize target information from a global perspective. Additionally, the replacement of standard Convolution (Conv) modules with Global Sparse Convolution (GSConv) modules in the Neck section effectively reduces computational costs while sustaining overall performance efficacy. The experimental results show that the detection system achieved a comprehensive accuracy rate of 99.2% and an F1 score of 99.29. The system possesses high accuracy and stability, enabling flexible and intelligent target detection applications in the automotive industry.
An Architectural Solution to a Biological Problem: A Systematic Review of Lighting Designs in Healthcare Environments
Authors: Hosseini Seyedeh Nazli , Walton James C. , SheikhAnsari Iman , Kreidler Nicole , Nelson Randy J.
Published: March 2024

Neuroscience and biological evidence emphasizes the profound influence of natural light on human health, offering benefits such as reducing fatigue, heightened alertness in healthcare providers, and improving patient outcomes. The objective of this review is to identify scientific studies and research to evaluate and report evidence of indoor lighting conditions’ influence on health outcomes, which can be used to develop lighting designs that align circadian rhythms in healthcare settings. A comprehensive search was conducted to identify rigorous empirical studies focused on the link between interior lighting conditions with health outcomes in the healthcare environment. For a comprehensive review of the existing literature, a four-phased methodology was employed including literature search, screening, and selection. Literature appraisals were conducted to determine the relevance and quality of evidence for each study identified. In addition, using a thematic analysis, patterns were identified, analyzed, and interpreted within the literature review. Accordingly, the results were organized into two main groups interventional human subjects and simulation-based studies. Despite evidence that natural light influences human health and happiness, a synthesis of reviewed studies suggests that the evidence for the benefits of artificial lighting in healthcare settings is less conclusive, with potential factors including variations in lighting design, inconsistent implementation of lighting interventions, and differing sample populations across studies. We conclude with an executive summary suggesting that future research should use standardized metrics and methods to focus on bridging the gap between theoretical understanding and practical application in lighting design for healthcare environments. Collaboration among architects, designers, lighting experts, and healthcare professionals can address these factors contributing to building a stronger evidence-based design for the benefits of artificial lighting in healthcare settings.
Cable-Driven Mechanism Models for Sensitive and Actuated Minimally Invasive Robotic Instruments
Authors: Muscolo Giovanni Gerardo , Fiorini Paolo
Published: March 2024

Cable-driven mechanism models are, usually, included in actuated systems; however, recently, their use for sensitive systems has been explored. In this paper, two cable-driven multi-body mechanism models are compared, underlining advantages and constraints in using sensitive cable-driven mechanisms for minimally invasive robotic instruments. The proposed approach could be useful in bypassing sterilization problems for surgical robotic instruments because our system allows for the separation of the robotic sterilizable part from the sensitive-actuated part of the surgical instrument. The real implementation of the proposed mechanism models, presented partially in other works, are validated in this paper, performing a simulation using a multi-body environment. Results confirm the feasibility of the proposed sensitive-actuated approach, defining new bases for the next challenges of the future.
Effects of the Surface Type on the Sprint Force–Velocity–Power Profile of Female Beach Handball Top-Level Players
Authors: Lara-Cobos Daniel , Martínez-Aranda Luis Manuel , Sanz-Matesanz Manuel , Cuadrado-Peñafiel Víctor , Ortega-Becerra Manuel
Published: March 2024

Beach handball (BH) is characterized by high-intensity actions, such as accelerations and short rest times, in combination with long periods of low-intensity activity during a match. The purpose of this study was to establish a comparative analysis between the effect of a hard surface vs. sandy surface on the properties of the sprint Force–Velocity–Power Profile (FVP) of female beach handball top-level players. Fourteen female BH players participated in this research. A cross-sectional investigation was performed in order to evaluate the determining variables of the FVP profile for different surfaces. After a specific warm-up, two maximal 20–30 m sprints (4 min resting between trials) were performed in two conditions (hard surface and sand) within 10 min. The female BH players showed higher mean values for all the FVP profile variables (p < 0.001) on the hard surface compared to sand, in addition to lower values for the 5 m (ES = 2.29 to 3.89) and 20 m sprinting times (ES = 2.39 to 3.99) (p < 0.001). However, the decrease in the ratio of force over acceleration was not discriminant between the surfaces. Positive correlations were found for the speed variables (0.691–0.807, p < 0.01), as well as the Pmax (0.520, p = 0.035), between the surfaces. A prior knowledge of the FVP profile for hard–sandy surfaces could offer an important reference value about the sprint properties of this population, and be useful for evaluating the efficiency, as well as the effect on the sprint and gaming performance, of specifically oriented training programs based on those reference values.
Automatic Translation between Mixtec to Spanish Languages Using Neural Networks
Authors: Santiago-Benito  Hermilo , Córdova-Esparza  Diana-Margarita , Castro-Sánchez  Noé-Alejandro , García-Ramirez  Teresa , Romero-González  Julio-Alejandro , Terven  Juan
Published: March 2024

This paper introduces a novel method for collecting and translating texts from the Mixtec to the Spanish language. The method comprises four primary steps. First, we collected a Mixtec–Spanish corpus that includes 4568 sentences from educational and religious domain texts. To enhance the parallel corpus, we generate synthetic data with GPT-3.5. Second, we cleaned the data with a semi-automatic approach followed by preprocessing and tokenization. In preprocessing, we removed stop words, duplicated sentences, special characters, and numbers and converted them to lowercase. Third, we performed semi-automatic alignment to find the correspondence of Mixtec–Spanish sentences to generate sentence-level aligned texts necessary for translation. Finally, we trained automatic translation models based on recurrent neural networks, bidirectional recurrent neural networks, and Transformers. Our system achieved a BLEU score of 95.66 for Mixtec-to-Spanish translation and 99.87 for Spanish-to-Mixtec translation. We also obtained a translation edit rate (TER) of 0.5 for Spanish-to-Mixtec and a TER of 16.5 for Mixtec-to-Spanish. Our research stands out as a pioneering effort in the field of automatic Mixtec-to-Spanish translation in Mexico, filling a gap identified in the current literature.
Simulation of a Novel Integrated Multi-Stack Fuel Cell System Based on a Double-Layer Multi-Objective Optimal Allocation Approach
Authors: Gao Jianhua , Zhou Su , Lu Yanda , Shen Wei
Published: March 2024

A multi-stack fuel cell system (MFCS) is a promising solution for high-power PEM fuel cell applications. This paper proposes an optimized stack allocation approach for power allocation, considering economy and dynamics to establish integrated subsystems with added functional components. The results show that an MFCS with target powers of 20 kW, 70 kW, and 120 kW satisfies lifetime and efficiency factors. The common rail buffer at the air supply subsystem inlet stabilizes pressure, buffers, and diverts. By adjusting the volume of the common rail buffer, it is possible to reduce the maximum instantaneous power and consumption of the air compressor. The integrated hydrogen supply subsystem improves hydrogen utilization and reduces parasitic power consumption. However, the integrated thermal subsystem does not have the advantages of integrated gas supply subsystems, and its thermal management performance is worse than that of a distributed thermal subsystem. This MFCS provides a solution for high-power non-average distribution PEM fuel cell systems.
Study of the Interrelations of the Concentrations of Six Tree Pollen Types and Six Atmospheric Pollutants with Rhinitis and Allergic Conjunctivitis in the Community of Madrid
Authors: Chico-Fernández Javier , Ayuga-Téllez Esperanza
Published: March 2024

Allergic pathologies of aerobiological origin, specifically those caused by exposure to pollen allergens, have shown a growing trend in recent decades worldwide. This trend is most evident in urban areas experiencing an incessant expansion of their territory. Several studies have shown an interaction between atmospheric pollutants and pollen grains, which implies a potentiation of the allergenicity of the latter. This study aims to analyze the possible influence, in the Community of Madrid (CAM), of the concentrations of six atmospheric pollutants (O3, particles PM10 and PM2.5, NO2, CO, and SO2), and of the pollen concentrations of six types of tree pollen (Cupressaceae, Olea, Platanus, Pinus, Ulmus, and Populus) on the episodes of attention of two pathologies, rhinitis and allergic conjunctivitis. The data collected came from the Air Quality Networks of the CAM and the Madrid City Council, the Palynological Network of the CAM, and the General Subdirectorate of Epidemiology of the Health Department of the CAM. Descriptive multiple linear regression models were used to analyze the interrelationships of the three variables. In most of the calculations performed, the adjusted R2 value is higher than 30%, and, in all cases, the p-values of the models obtained are less than 0.0001. All the models performed in the study period for allergic rhinitis indicate a reasonable correlation, and this is also true for almost all of the models calculated for allergic conjunctivitis. Moreover, it is allergic rhinitis for which the highest values of adjusted R2 were obtained. Pinus is the pollen type most frequently interrelated with conjunctivitis and allergic rhinitis (followed in both cases by Olea and Populus) throughout the study years. In this same period, O3 is the air pollutant most frequently present in the models calculated for allergic conjunctivitis (followed by NO2 and PM10), while particle PM10 is the most frequently included in the calculations made for allergic rhinitis, followed by O3 and SO2.
Applied Theatre: Research-Based Theatre, or Theatre-Based Research? Exploring the Possibilities of Finding Social, Spatial, and Cognitive Justice in Informal Housing Settlements in India, or Tales from the Banyan Tree
Authors: Busby Selina
Published: March 2024

This article draws on a twenty-year relationship of short-term interventions with Dalit communities living in informal settlements, sub-cities and urban villages in Mumbai, that have sought to create public theatre events based on research by and with communities that celebrate, problematise and interrogate sustainable urban living. In looking back over the developments and changes to our working methods in Mumbai, I explore how the projects priorities the roles of the community as both researchers and artists. I consider where a specific applied theatre project, which focuses on site specific storytelling with Dalit communities in Worli Koliwada and Dharavi, functions on a continuum of interactive, participatory, and emancipatory practice, research and performance. Applied Theatre practices should not and cannot remain static, they need to be constantly reformed and as practitioners and researchers we need to constantly re-examine the ways in which we work. This chapter poses two central questions: firstly, can this long-term partnership between practitioners, researchers and artists from the UK and India working with community members genuinely be a space for co-creating knowledge and theatre? And secondly, if so, is this Theatre-based Research or Research Based Theatre? I interrogate Applied Theatre’s potential to create a space of cognitive justice, which must be the next step for applied theatre, along-side its more widely accepted aims of searching for social and spatial justice and which places the community as both artists and researchers. The Dalit social reality is one of oppression, based on three axes: social, economic and gender. The chapter explores how working as co-researchers and the public performance of their stories has been a form of ‘active citizenship’ for these participants and is a key part of their strategy in their demand for policy changes. In looking forward I ask how working in international partnerships with community members can promote cognitive justice and go beyond a merely participatory practice. I consider why it is vital for the field that applied theatre practice includes partners from both the global south and north working together to co-create knowledge, new methods of practice to ensure an applied theatre knowledge democracy. In doing so I will discuss if and how this work might be considered to be Theatre-based Research.
“Spaces of Silence” and “Secret Music of the Word”: Verbo-Musical Minimalism in the Poetry of Gennady Aygi and Elizaveta Mnatsakanova
Authors: Sokolova Olga , Feshchenko Vladimir
Published: March 2024

Two major poets of the Russian Neo-Avant-Garde—Gennady Aygi and Elizaveta Mnatsakanova—created textual works that transgressed the limits of language and the borders between the arts. Each pursued their own method of the visualization and musicalization of verbal matter, yet both share a particular musical sensibility, which guarantees the integrity of the linguistic structure of their verse, despite the fragmentation and logical incoherence of its elements. The atonal (serial) musical tradition has a special significance for these experimental poetics of minimalism. Mnatsakanova, herself a musicologist, who was friends with Dmitri Shostakovich, not only used the techniques of contemporary music composition in her visual and sound poetry, but also collaborated with electronic musicians in her recorded poetry performances. Aygi experimented with language, not only crossing the boundaries between music and poetry, but also between sound and silence. For him, music was a way of expressing pre-verbal subjectivity and reproducing signs of meaning that are hidden from ordinary perception. In his poems, Aygi brought together Chuvash folk music with experimental techniques of minimalism, correlating his own work with such Soviet unofficial composers as Andrey Volkonsky and Sofia Gubaidulina. This paper will address the issues of transmutation between verbal, visual, and sound art in poetic minimalism of the Soviet-era underground.
Impact of Urban Forest and Park on Air Quality and the Microclimate in Jinan, Northern China
Authors: Liu Kun , Li Juan , Sun Lei , Yang Xueqiao , Xu Chongqing , Yan Guihuan
Published: March 2024

Though the impact of urban vegetation on air quality and the microclimate has attracted increasing attention, there have been few studies quantitatively assessing this impact in North China, where air pollution is severe. In this study, we investigated the impact of urban forests and urban parks on air quality and the microclimate in Jinan, northern China. Six sites were chosen to represent urban forest, urban park, and downtown areas, respectively. The results indicate that urban forest can effectively reduce PM2.5 and ozone (O3) concentrations in the warm season, when temperatures are higher and plants are lush. The PM2.5 and O3 concentrations in the urban forest areas were 6.3–6.5 μg m−3 and 21–23 μg m−3 lower than those in downtown areas during the period of 10:00–15:00. In contrast, urban park areas can reduce PM2.5 concentrations but have little impact on gaseous pollutants such as nitrogen dioxide and O3. Furthermore, both urban forest and urban park areas reduced temperatures, by approximately 4.1–6.8 °C and 1.36 °C, respectively, and increased relative humidity, by about 13.4–12.9% and 0.9%, promoting a more comfortable thermal environment for residents. Therefore, this study highlights the crucial role of urban vegetation in improving air quality and creating a comfortable environment for residents.
Biomass Combustion in Boiler: Environmental Monitoring of Sugar Markers and Pollutants
Authors: Paris Enrico , Carnevale Monica , Palma Adriano , Vincenti Beatrice , Salerno Mariangela , Proto Andrea Rosario , Papandrea Salvatore , Guerriero Ettore , Perilli Mattia , Cerasa Marina , Di Stefano Valerio , Gallucci Francesco
Published: March 2024

The need to use renewable sources and matrices with energy potential is widely recognized. The development of innovative technologies aimed at the improvement of energy conversion processes and reducing environmental impacts is currently receiving increasing attention from the scientific community and policymakers. The presence of sugars in airborne particle materials is attributed to biomass combustion. For this reason, these compounds are considered markers of biomass burning. The purpose of this work was to evaluate the emissions produced by agroforestry biomass burning (citrus pruning) by simultaneously sampling both stack emissions and atmospheric particulates in the area around a biomass boiler to understand the real contribution of biomass burning to atmospheric pollution. The combustion tests were carried out by comparing the processes with and without particulate abatement system to see how biomass combustion’s contribution to particulate emission can be controlled and reduced. During the tests, the focus was on particulate matter (PM) speciation in terms of sugar marker identification and determination. This study aims to increase knowledge to better understand the contribution of biomass plants to air pollution and differentiate it from the contributions of other sources, such as vehicular traffic or domestic heating.
Tracking Carbon Dioxide with Lagrangian Transport Simulations: Case Study of Canadian Forest Fires in May 2021
Authors: Liao Ye , Deng Xuying , Huang Mingming , Liu Mingzhao , Yi Jia , Hoffmann Lars
Published: March 2024

The large amounts of greenhouse gases, such as carbon dioxide, produced by severe forest fires not only seriously affect the ecosystems in the area where the fires occur but also cause a greenhouse effect that has a profound impact on the natural environment in other parts of the world. Numerical simulations of greenhouse gas transport processes are often affected by uncertainties in the location and timing of the emission sources and local meteorological conditions, and it is difficult to obtain accurate and credible predictions by combining remote sensing satellite data with given meteorological forecasts or reanalyses. To study the regional transport processes and impacts of greenhouse gases produced by sudden large-scale forest fires, this study applies the Lagrangian particle dispersion model Massive-Parallel Trajectory Calculations (MPTRAC) to conduct forward simulations of the CO2 transport process of greenhouse gases emitted from forest fires in the central region of Saskatchewan, Canada, during the period of 17 May to 25 May 2021. The simulation results are validated with the Orbiting Carbon Observatory-2 Goddard Earth Observing System (OCO-2 GEOS) Level 3 daily gridded CO2 product over the study area. In order to leverage the high computational costs of the numerical simulations of the model, we implement the forward simulations on the Tianhe-2 supercomputer platform and the JUWELS HPC system, which greatly improves the computational efficiency through parallel computation and makes near-real-time predictions of atmospheric transport processes feasible.
Measurement and Analysis of Brake and Tyre Particle Emissions from Automotive Series Components for High-Load Driving Tests on a Wheel and Suspension Test Bed
Authors: Kupper Martin , Schubert Ludwig , Nachtnebel Manfred , Schröttner Hartmuth , Huber Michael Peter , Fischer Peter , Bergmann Alexander
Published: March 2024

A current challenge in realising clean road transport is non-exhaust emissions. Important advances regarding measurement systems, including well-defined characterisation techniques, as well as regulation, will be made in the next few years. In this work, we present the detailed results of particle emission analyses, consisting of aerosol (size distribution, particle number (PN), and mass (PM)) and electron microscopy (EM) measurements, under different load conditions on a test bed for a wheel suspension and brakes. Standard tyres and brakes from serial production were tested with a high-load driving cycle, while particle measurements were conducted by gravimetric measurements and with a TSI SMPS, a TSI APS, and a GRIMM OPS. Furthermore, samples were analysed by electron microscopy. A bimodal particle size distribution (PSD) was obtained with an SMPS, with peaks at 20 nm and around 400 nm. The results of an EM analysis of >1400 single particles from the electrostatic sampler match the PSD results. The EM analysis also showed ultrafine particles, mainly containing O, Fe, Si, Ba, Mg, and S, and also fractal particles with high-C fractions. Our results suggest, in agreement with the previously published literature, that particulate emissions are related to the brake disc temperature and occur in significant amounts above a threshold temperature.
CMIP6 Simulation-Based Daily Surface Air Temperature and Precipitation Projections over the Qinghai-Tibetan Plateau in the 21st Century
Authors: Wang Kangming , Song Xinyi , Lu Fan , Yu Songbin , Zhou Yuyan , Sun Jin
Published: March 2024

The Qinghai-Tibetan Plateau (QTP), the source of many major Asian rivers, is sensitive to climate change, affecting billions of people’s livelihoods across Asia. Here, we developed high-resolution projections of precipitation and daily maximum/minimum temperatures at 0.1° spatial resolution over the QTP. The projections are based on the output from seven global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) for historical (1979–2013) and projected (2015–2100) climates across four scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). An updated nonstationary cumulative distribution function matching method (called CNCDFm) was used to remove model systemic bias. We verify the necessity of taking into account altitude in downscaling processes and the validity of nonstationary bias correction. Compared to the historical period, the climate in the QTP in the 21st century is warmer (1.2–5.1 °C, for maximum surface temperature) and wetter (3.9–26.8%) according to the corrected GCM projection. For precipitation, the Indus River (IDR), Tarim River (TMR), Inner of Qiangtang Basin (IQTB), Yarlung Zangbo (YLZBR), and Qaidam Basin (QDB) showed growth well above the global average across high radiative forcing scenarios, which could have a profound impact on the regional hydrological cycle. However, there is great uncertainty in precipitation prediction, which is demonstrated by a very low signal-to-noise ratio (SNR) and a large difference between Bayesian model averaging (BMA) and multi-model averages (MMAs). This bias-corrected dataset is available for climate change impact research in the QTP at the subregion scale.
Impact of the No-Driving Day Program on Air Quality in a High-Altitude Tropical City: The Case of the Toluca Valley Metropolitan Area
Authors: Garcia Agustin , Almanza Victor , Tejeda Dzoara , Alvarado-Castillo Mauro
Published: March 2024

This study addresses the pressing issue of urban air pollution impact, emphasizing the need for emissions control to ensure environmental equity. Focused on the Toluca Valley Metropolitan Area (TVMA), this research employs air quality modeling to examine ozone, sulfur dioxide, nitrogen dioxide, and carbon monoxide concentrations during three different periods in 2019. It quantitatively assesses the performance of a state-of-the-art air quality model while evaluating the efficacy of a No-Driving day mitigation measure program, similar to the one which is currently implemented in Mexico City. Using an updated national emissions inventory for 2016, this study highlights the model capability of representing ozone formation and shows that reducing mobile emissions of key pollutants contributes to lowering downwind surface ozone levels, albeit with a minimal local impact. The insights and tools from this work hold potential value for decision-making in the broader Megalopolis context, aligning with global efforts to comprehend and mitigate urban air pollution impacts.
Exploring Explicit Definite Integral Formulae with Trigonometric and Hyperbolic Functions
Authors: Chen Yulei , Guo Dongwei
Published: March 2024

Making use of integration by parts and variable replacement methods, we derive some interesting explicit definite integral formulae involving trigonometric or hyperbolic functions, whose results are expressed in terms of Catalan’s constant, Dirichlet’s beta function, and Riemann’s zeta function, as well as π in the denominator.
Assessment of Run-Off Waters Resulting from Lithium-Ion Battery Fire-Fighting Operations
Authors: Bordes Arnaud , Papin Arnaud , Marlair Guy , Claude Théo , El-Masri Ahmad , Durussel Thierry , Bertrand Jean-Pierre , Truchot Benjamin , Lecocq Amandine
Published: March 2024

As the use of Li-ion batteries is spreading, incidents in large energy storage systems (stationary storage containers, etc.) or in large-scale cell and battery storages (warehouses, recyclers, etc.), often leading to fire, are occurring on a regular basis. Water remains one of the most efficient fire extinguishing agents for tackling such battery incidents, and large quantities are usually necessary. Since batteries contain various potentially harmful components (metals and their oxides or salts, solvents, etc.) and thermal-runaway-induced battery incidents are accompanied by complex and potentially multistage fume emissions (containing both gas and particles), the potential impact of fire run-off waters on the environment should be considered and assessed carefully. The tests presented in this paper focus on analyzing the composition of run-off waters used to spray NMC Li-ion modules under thermal runaway. It highlights that waters used for firefighting are susceptible to containing many metals, including Ni, Mn, Co, Li and Al, mixed with other carbonaceous species (soot, tarballs) and sometimes undecomposed solvents used in the electrolyte. Extrapolation of pollutant concentrations compared with PNEC values showed that, for large-scale incidents, run-off water could be potentially hazardous to the environment.
The Role of AI in Hospitals and Clinics: Transforming Healthcare in the 21st Century
Authors: Maleki Varnosfaderani Shiva , Forouzanfar Mohamad
Published: March 2024

As healthcare systems around the world face challenges such as escalating costs, limited access, and growing demand for personalized care, artificial intelligence (AI) is emerging as a key force for transformation. This review is motivated by the urgent need to harness AI’s potential to mitigate these issues and aims to critically assess AI’s integration in different healthcare domains. We explore how AI empowers clinical decision-making, optimizes hospital operation and management, refines medical image analysis, and revolutionizes patient care and monitoring through AI-powered wearables. Through several case studies, we review how AI has transformed specific healthcare domains and discuss the remaining challenges and possible solutions. Additionally, we will discuss methodologies for assessing AI healthcare solutions, ethical challenges of AI deployment, and the importance of data privacy and bias mitigation for responsible technology use. By presenting a critical assessment of AI’s transformative potential, this review equips researchers with a deeper understanding of AI’s current and future impact on healthcare. It encourages an interdisciplinary dialogue between researchers, clinicians, and technologists to navigate the complexities of AI implementation, fostering the development of AI-driven solutions that prioritize ethical standards, equity, and a patient-centered approach.
Research and Development of a 3D-Printed Dynamic Finger Flexion Orthosis for Finger Extension Stiffness—A Preliminary Study
Authors: Yu June-Tzu , Huang Yi-Chao , Chen Chen-Sheng
Published: March 2024

Finger extension stiffness is a common post-traumatic complication that results in the hand’s functional impairment. In clinical practice, a dynamic splint enables the patient to stretch the affected finger independently. However, current dynamic splints have drawbacks, such as limited stretching efficacy, and interfere with the hand’s functional activities. Therefore, this study aimed to develop a dynamic finger flexion orthosis capable of stretching each finger joint using additive manufacturing (AM) technology, thereby enabling hand functional activity, and analyze the clinical improvement in the range of motion (ROM). One subject with a hand fracture was recruited while undergoing a 7-week home-based rehabilitation program for the orthosis. The outcome measurements included the total active motion (TAM), the tip-to-finger distance (TPD), and the score on the Disability of Arm, Shoulder, and Hand (DASH) questionnaire. The results show that the TAM of the participant’s fingers increased by 72.7 degrees on average, the TPD decreased by 3.5 cm on average, and the DASH score decreased to 9.5 points. The 7-week home-based rehabilitation program for the orthosis resulted in a 53.6% increase in the TAM on average. The developed orthosis improved hand function and enabled a more complete ROM in finger flexion.
A Privacy-Preserving Approach to Effectively Utilize Distributed Data for Malaria Image Detection
Authors: Kareem Amer , Liu Haiming , Velisavljevic Vladan
Published: March 2024

Malaria is one of the life-threatening diseases caused by the parasite known as Plasmodium falciparum, affecting the human red blood cells. Therefore, it is an important to have an effective computer-aided system in place for early detection and treatment. The visual heterogeneity of the malaria dataset is highly complex and dynamic, therefore higher number of images are needed to train the machine learning (ML) models effectively. However, hospitals as well as medical institutions do not share the medical image data for collaboration due to general data protection regulations (GDPR) and the data protection act (DPA). To overcome this collaborative challenge, our research utilised real-time medical image data in the framework of federated learning (FL). We have used state-of-the-art ML models that include the ResNet-50 and DenseNet in a federated learning framework. We have experimented both models in different settings on a malaria dataset constituting 27,560 publicly available images and our preliminary results showed that the DenseNet model performed better in accuracy (75%) in contrast to ResNet-50 (72%) while considering eight clients, while the trend was observed as common in four clients with the similar accuracy of 94%, and six clients showed that the DenseNet model performed quite well with the accuracy of 92%, while ResNet-50 achieved only 72%. The federated learning framework enhances the accuracy due to its decentralised nature, continuous learning, and effective communication among clients, as well as the efficient local adaptation. The use of federated learning architecture among the distinct clients for ensuring the data privacy and following GDPR is the contribution of this research work.
Quantitative Assessment of Acetabular Defects in Revision Hip Arthroplasty Based on 3D Modeling: The Area Increase Ratio (AIR) Method
Authors: Marongiu Giuseppe , Campacci Antonio , Capone Antonio
Published: March 2024

The most common classifications for acetabular bone defects are based on radiographic two-dimensional imaging, with low reliability and reproducibility. With the rise of modern processing techniques based on 3D modelling, methodologies for the volumetric quantification of acetabular bone loss are available. Our study aims to describe a new methodology for the quantitative assessment of acetabular defects based on 3D modelling, focused on surface analysis of the integrity of the main anatomical structures of the acetabulum represented by four corresponding sectors (posterior, superior, anterior, and medial). The defect entity is measured as the area increase ratio (AIR) detected in all the sectors analyzed on three planes of view (frontal, sagittal, and axial) compared to healthy hemipelvises. The analysis was performed on 3D models from the CT-scan of six exemplary specimens with a unilateral pathological hemipelvis. The AIR between the native and the pathological hemipelvis was calculated for each sector, for a total of 48 analyses (range, +0.93–+171.35%). An AIR of >50% were found in 22/48 (45.8%) sectors and affected mostly the posterior, medial, and superior sectors (20/22, 90.9%). Qualitative analysis showed consistency between the data and the morphological features of the defects. Further studies with larger samples are needed to validate the methodology and potentially develop a new classification scheme.
Applications of Large Language Models in Pathology
Authors: Cheng Jerome
Published: March 2024

Large language models (LLMs) are transformer-based neural networks that can provide human-like responses to questions and instructions. LLMs can generate educational material, summarize text, extract structured data from free text, create reports, write programs, and potentially assist in case sign-out. LLMs combined with vision models can assist in interpreting histopathology images. LLMs have immense potential in transforming pathology practice and education, but these models are not infallible, so any artificial intelligence generated content must be verified with reputable sources. Caution must be exercised on how these models are integrated into clinical practice, as these models can produce hallucinations and incorrect results, and an over-reliance on artificial intelligence may lead to de-skilling and automation bias. This review paper provides a brief history of LLMs and highlights several use cases for LLMs in the field of pathology.
Validation and Estimation of Obesity-Induced Intervertebral Disc Degeneration through Subject-Specific Finite Element Modelling of Functional Spinal Units
Authors: Singh Nitesh Kumar , Singh Nishant K. , Verma Rati , Diwan Ashish D.
Published: March 2024

(1) Background: Intervertebral disc degeneration has been linked to obesity; its potential mechanical effects on the intervertebral disc remain unknown. This study aimed to develop and validate a patient-specific model of L3–L4 vertebrae and then use the model to estimate the impact of increasing body weight on disc degeneration. (2) Methods: A three-dimensional model of the functional spinal unit of L3–L4 vertebrae and its components were developed and validated. Validation was achieved by comparing the range of motions (RoM) and intradiscal pressures with the previous literature. Subsequently, the validated model was loaded according to the body mass index and estimated stress, deformation, and RoM to assess disc degeneration. (3) Results: During validation, L3–L4 RoM and intradiscal pressures: flexion 5.17° and 1.04 MPa, extension 1.54° and 0.22 MPa, lateral bending 3.36° and 0.54 MPa, axial rotation 1.14° and 0.52 MPa, respectively. When investigating the impact of weight on disc degeneration, escalating from normal weight to obesity reveals an increased RoM, by 3.44% during flexion, 22.7% during extension, 29.71% during lateral bending, and 33.2% during axial rotation, respectively. Also, stress and disc deformation elevated with increasing weight across all RoM. (4) Conclusions: The predicted mechanical responses of the developed model closely matched the validation dataset. The validated model predicts disc degeneration under increased weight and could lay the foundation for future recommendations aimed at identifying predictors of lower back pain due to disc degeneration.
Identification and Validation of eRNA as a Prognostic Indicator for Cervical Cancer
Authors: Huang Lijing , Zhang Jingkai , Songyang Zhou , Xiong Yuanyan
Published: March 2024

The survival of CESC patients is closely related to the expression of enhancer RNA (eRNA). In this work, we downloaded eRNA expression, clinical, and gene expression data from the TCeA and TCGA portals. A total of 7936 differentially expressed eRNAs were discovered by limma analysis, and the relationship between these eRNAs and survival was analyzed by univariate Cox hazard analysis, LASSO regression, and multivariate Cox hazard analysis to obtain an 8-eRNA model. Risk score heat maps, KM curves, ROC analysis, robustness analysis, and nomograms further indicate that this 8-eRNA model is a novel indicator with high prognostic performance independent of clinicopathological classification. The model divided patients into high-risk and low-risk groups, compared pathway diversity between the two groups through GSEA analysis, and provided potential therapeutic agents for high-risk patients.
Age and Sex in the Development of Hepatic Encephalopathy: Role of Alcohol
Authors: Tong Xiao , Hussain Hussain , Shamaladevi Nagarajarao , Norenberg Michael , Fadel Aya , El Hiba Omar , Abdeljalil El , El-Mansoury Bilal , Kempuraj Deepak , Natarajan Sampath , Schally Andrew , Jaszberenyi Miklos , Salgueiro Luis , Paidas Michael , Jayakumar Arumugam
Published: March 2024

Hepatic encephalopathy (HE) is a neurological condition linked to liver failure. Acute HE (Type A) occurs with acute liver failure, while chronic HE (Type C) is tied to cirrhosis and portal hypertension. HE treatments lag due to gaps in understanding its development by gender and age. We studied how sex and age impact HE and its severity with combined liver toxins. Our findings indicate that drug-induced (thioacetamide, TAA) brain edema was more severe in aged males than in young males or young/aged female rats. However, adding alcohol (ethanol, EtOH) worsens TAA’s brain edema in both young and aged females, with females experiencing a more severe effect than males. These patterns also apply to Type A HE induced by azoxymethane (AZO) in mice. Similarly, TAA-induced behavioral deficits in Type C HE were milder in young and aged females than in males. Conversely, EtOH and TAA in young/aged males led to severe brain edema and fatality without noticeable behavioral changes. TAA metabolism was slower in aged males than in young or middle-aged rats. When TAA-treated aged male rats received EtOH, there was a slow and sustained plasma level of thioacetamide sulfoxide (TASO). This suggests that with EtOH, TAA-induced HE is more severe in aged males. TAA metabolism was similar in young, middle-aged, and aged female rats. However, with EtOH, young and aged females experience more severe drug-induced HE as compared to middle-aged adult rats. These findings strongly suggest that gender and age play a role in the severity of HE development and that the presence of one or more liver toxins may aggravate the severity of the disease progression.
Sleep and Thermoregulation in Birds: Cold Exposure Reduces Brain Temperature but Has Little Influence on Sleep Time and Sleep Architecture in Jackdaws (Coloeus monedula)
Authors: van Hasselt Sjoerd J. , Coscia Massimiliano , Allocca Giancarlo , Vyssotski Alexei L. , Meerlo Peter
Published: March 2024

Birds have an electrophysiological sleep state that resembles mammalian rapid-eye-movement (REM) sleep. However, whether its regulation and function are similar is unclear. In the current experiment, we studied REM sleep regulation in jackdaws (Coloeus monedula) by exposing the birds to low ambient temperature, a procedure that selectively suppresses REM sleep in mammals. Eight jackdaws were equipped with electrodes to record brain activity and neck muscle activity and a thermistor to record cortical brain temperature. Recordings covered a three-day period starting with a 24 h baseline day at an ambient temperature of 21 °C, followed by a 12 h cold night at 4 °C, after which the ambient temperature was restored to 21 °C for the remaining recovery period. Cold exposure at night caused a significant drop in brain temperature of 1.4 °C compared to the baseline night. However, throughout the cold night, jackdaws expressed NREM sleep and REM sleep levels that were not significantly different from the baseline. Also, EEG spectral power during NREM sleep was unaffected by cold exposure. Thus, while cold exposure had a clear effect on brain temperature in jackdaws, it did not have the same REM sleep suppressing effect reported for mammals. These findings suggest that the REM-sleep-like state in birds, unlike REM sleep in mammals, is protected against the influence of low temperature.