bluuebunny/crossref_metadata_2025_split huggingface dataset:
Additive Manufacturing of Metal Load‐Bearing Implants 2: Surface Modification and Clinical Challenges
Authors: Zanetti Elisabetta M. , Fragomeni Gionata , Sanguedolce Michela , Pascoletti Giulia , Napoli Luigi De , Filice Luigino , Catapano Gerardo 
Published: February 2024

AbstractAdditive manufacturing (AM) permits sustainable production of personalized load‐bearing metal implants with complex structures. Regulations prescribe that implants have to meet strict requirements to not harm patients, and production technique should allow the certification of their performance. Process, materials, operating parameters, and customization to patient's needs could limit AM. Layer‐by‐layer material deposition and repeated thermal cycles may make outer surface of AM implants chemically and physically uneven and rough, eliciting biological response of host tissue and hindering therapeutic success. In this paper, we discuss the clinical challenges that AM must overcome to replace traditional techniques in implant and prostheses design.
Cocatalyst Modified Polymeric Carbon Nitride Photoanode for Enhanced Photoelectrochemical Properties
Authors: Yang Xuerong , Lv Xiaowei , Tong Kun , Peng Mengyang , He Zeyao , Sun Panpan , Sun Xiaohua 
Published: February 2024

AbstractAs a new organic photocatalyst, polymeric carbon nitride (CN) has shown good application potential in the field of photoelectrochemistry due to its unique physical and chemical properties, but its application has been seriously hindered due to its inherent characteristics such as the difficulty in charge separation. In this study, FeOOH modified CN photoanode (CN−Fe) was constructed to investigate the effect of the cocatalyst on the charge injection capacity of organic semiconductor photoelectrodes. The experimental results demonstrate significant improvement in the charge injection efficiency of the photoanode due to the introduction of FeOOH cocatalyst, leading to enhanced photoelectrochemical performance with approximately 2.4 times increase in photocurrent density. By thoroughly investigating the mechanism behind the loading of FeOOH on the polymeric carbon nitride photoanode, we gained profound insights into the behavior of charge carriers and reaction kinetics during the photoelectrocatalytic process.
A longitudinal analysis of the impact of nonsurgical and surgical treatment of peri‐implantitis upon clinical parameters and implant stability quotient values. A 2–3‐year follow‐up
Authors: Harrison Peter , Madeley Edward , Nolan Michael , Renvert Stefan , Polyzois Ioannis 
Published: February 2024

AbstractObjectivesIn this study, the aim was to investigate the medium‐ to long‐term impact of peri‐implantitis treatment upon clinical parameters and implant stability quotient values and to ascertain if magnetic resonance frequency analysis can be used as a diagnostic tool to demonstrate postoperative healing following treatment of peri‐implantitis.Materials and MethodsA total of n = 26 patients (n = 86 implants) diagnosed with peri‐implantitis were recruited for this prospective cohort study and four different treatment modalities were used. Baseline measurements of a number of clinical parameters as well as implant stability measurements in the form of ISQ were recorded. These measurements were repeated at 6, 12, and 24–36 months following treatment. Analysis of variance was performed for all implants treated as well as separately for each treatment modality. A regression model was also used to determine factors affecting ISQ measurements over time.ResultsTreatment of peri‐implantitis resulted in significant improvements of both average PPDs and BOP (p < .0001 and p < .01). ISQ values marginally improved initially for all treatment modalities, but improvement was only maintained for 2–3 years in treatment modalities I (+1.28), III (+1.49), and IV (+2.92). There was a statistically significant negative linear correlation between average PPD and the ISQ values recorded both at baseline (r = −.618, p < 0.0001) and at 2/3 years (r = −.604, p < 0.0001).ConclusionOver the 2–3‐year follow‐up period, all four treatment modalities led to improved clinical and radiographic peri‐implant parameters but implant stability posttreatment, as indicated by the fact that the recorded ISQ scores remained stable. As a result, use of MRFA as an adjunct to the traditionally used periodontal and radiographic tools for the evaluation of postoperative implant stability following the treatment of peri‐implant disease cannot be recommended.
Occurrence and distribution of lost molars and furcation defects in a Bulgarian population: A retrospective three‐dimensional study
Authors: Maynalovska Hristina , Mlachkova Antoaneta , Voyslavov Tsvetomil , Kotsilkov Kamen 
Published: February 2024

AbstractObjectivesTo identify the ocuurrence, distribution, and factors associated with lost molars and furcation defects in a sample of the Bulgarian population.Material and MethodsThe full mouth cone‐beam computed tomography of 56 male and 57 female patients, aged between 19 and 84 years, were examined. A comprehensive evaluation was performed on a total of 675 molars—339 in maxilla and 336 in mandible. Associations with variables such as age, gender, and periodontal disease were analyzed.ResultsWith aging the number of missing teeth and interradicular lesions increased. No significant links between gender and molar loss (p = .64) or gender and furcation involvement (p = .25) was found. Periodontitis was strongly associated with both studied dental problems (p < .001). The occurrence of furcation defects was more frequently observed in the maxilla than in the mandible.ConclusionThe occurrence and distribution of lost molars and furcation defects is substantial within the studied sample. Further investigation with a larger patient cohort is needed. Pertinent healthcare strategies to address the observed dental health issues also have to be developed.
Limitations and Progresses in Carbon‐Based Cesium Lead Halide Perovskite Solar Cells
Authors: Wang Wenran , Zhang Jianxin , Guo Huishi , Pan Zhenxiao , Rao Huashang , Zhang Guizhi , Zhong Xinhua 
Published: February 2024

AbstractInorganic cesium lead halide perovskites (CsPbIxBr3−x, 0≤x≤3) are promising alternatives with great thermal stability. Additionally, the choice of moisture‐resistive and dopant‐free carbon as the electrode material can simultaneously solve the problems of stability and cost. Therefore, carbon electrode‐based inorganic PSCs (C‐IPSCs) represent a promising candidate for commercialization, yet both the efficiencies and stability of related devices demand further progress. This article reviews the recent advancement of C‐IPSCs and then unravels the distinctive merits and limitations in this field. Subsequently, our perspective on various modification strategies is analyzed on a methodological level. Finally, this article outlooks the promising research contents and the remaining unresolved issues in this field. We believe that understanding and analyzing the related problems in this field are instructive to stimulate the future development of C‐IPSCs.
Disease‐specific plasma protein profiles in patients with fever after traveling to tropical areas
Authors: Sundling Christopher , Yman Victor , Mousavian Zaynab , Angenendt Sina , Foroogh Fariba , von Horn Ellen , Lautenbach Maximilian Julius , Grunewald Johan , Färnert Anna , Sondén Klara 
Published: February 2024

AbstractFever is common among individuals seeking healthcare after traveling to tropical regions. Despite the association with potentially severe disease, the etiology is often not determined. Plasma protein patterns can be informative to understand the host response to infection and can potentially indicate the pathogen causing the disease. In this study, we measured 49 proteins in the plasma of 124 patients with fever after travel to tropical or subtropical regions. The patients had confirmed diagnoses of either malaria, dengue fever, influenza, bacterial respiratory tract infection, or bacterial gastroenteritis, representing the most common etiologies. We used multivariate and machine learning methods to identify combinations of proteins that contributed to distinguishing infected patients from healthy controls, and each other. Malaria displayed the most unique protein signature, indicating a strong immunoregulatory response with high levels of IL10, sTNFRI and II, and sCD25 but low levels of sCD40L. In contrast, bacterial gastroenteritis had high levels of sCD40L, APRIL, and IFN‐γ, while dengue was the only infection with elevated IFN‐α2. These results suggest that characterization of the inflammatory profile of individuals with fever can help to identify disease‐specific host responses, which in turn can be used to guide future research on diagnostic strategies and therapeutic interventions.
Indoor air quality in Kazakh households: Evaluating PM2.5 levels generated by cooking activities
Authors: Karaca Ferhat , Guney Mert , Agibayeva Akmaral , Otesh Nurlan , Kulimbet Mukhtar , Glushkova Natalya , Chang Yuefang , Sekikawa Akira , Davletov Kairat 
Published: February 2024

AbstractThe present study introduces a concentration estimation model for indoor inhalable fine particles (PM2.5) during cooking activities in typical Kazakh houses, which are generally poorly ventilated with high emission levels. The aim of the present work is to identify factors influencing PM2.5 concentrations during cooking and elucidate the mechanisms underlying the build‐up and reduction of PM2.5 concentrations. These are achieved through a methodology that combines PM2.5 sampling, monitoring, and modeling to predict household PM2.5 levels and estimate daily concentrations. Specifically, USEPA's IAQX v1.1 was employed to simulate the one‐zone concept (kitchen) for concentrations related to cooking activities in several households. The results reveal that PM2.5 concentrations varied between 13 and 266 μg/m3 during cooking activities. Factors such as kitchen size, air exchange characteristics, and the type of food and cooking style were identified as important, influencing the observed concentrations. The model accurately captured concentration trends (R > 0.9). However, certain predictions tended to overestimate the measurements, attributing to inaccuracies in selecting air exchange and emission rates. Cooking activities contributed to household air pollutant (HAP) PM2.5 levels ranging from 9% to 94%. Notably, during the non‐heating period of the year (corresponding to the warmer half of the year), the impact of cooking became more significant and was identified as a major contributor to indoor PM2.5 concentrations. Conversely, during the heating period (i.e., the colder part of the year), outdoor PM levels and household ventilation practices played primary roles in regulating indoor air concentrations. This present study presents one of the initial efforts to assess household air pollutants in Central Asia, providing foundation and insights into the indoor air quality of Kazakh houses, where the understanding of indoor air quality remains limited. Future research recommendations include developing advanced models that account for individual activity patterns and specific house types for improved accuracy and representativeness.
Deep‐Q‐Network hybridization with extended Kalman filter for accelerate learning in autonomous navigation with auxiliary security module
Authors: Bezerra Carlos Daniel de Sousa , Vieira Flávio Henrique Teles , Soares Anderson da Silva 
Published: February 2024

AbstractThis article proposes an algorithm for autonomous navigation of mobile robots that mixes reinforcement learning with extended Kalman filter (EKF) as a localization technique, namely EKF‐DQN, aiming to accelerate the maximization of the learning curve and improve the reward values obtained in the learning process. More specifically, Deep‐Q‐Networks (DQN) are used to control the trajectory of an autonomous robot in an environment with many obstacles. To improve navigation capability in this environment, we also propose a fusion of visual and nonvisual sensors. Due to the ability of EKF to predict states, this algorithm is used as a learning accelerator for the DQN network, predicting future states and inserting this information into the memory replay. Aiming to increase the safety of the navigation process, a visual safety system is also proposed to avoid collisions between the mobile robot and people circulating in the environment. The efficiency of the proposed control system is verified through computational simulations using the CoppeliaSIM simulator with code insertion in Python. The simulation results show that the EKF‐DQN algorithm accelerates the maximization of rewards obtained and provides a higher success rate in fulfilling the mission assigned to the robot when compared to other value‐based and policy‐based algorithms. A demo video of the navigation system can be seen at:
https://bit.ly/3reEZrU.
A two‐stage reliable computational scheme for stochastic unsteady mixed convection flow of Casson nanofluid
Authors: Nawaz Yasir , Arif Muhammad Shoaib , Nazeer Amna , Abbasi Javeria Nawaz , Abodayeh Kamaleldin 
Published: February 2024

AbstractResearchers can incorporate uncertainties in computational fluid dynamics (CFD) that go beyond the inaccuracies caused by numerical discretization thanks to stochastic simulations. This study confirms the validity of current stochastic modeling tools by providing examples of stochastic simulations in conjunction with numerical solutions for incompressible flows. A numerical technique for solving deterministic and stochastic models is developed in this work. Our approach employs the Euler‐Maruyama method for stochastic modeling, representing a stochastic version of the third‐order explicit‐implicit scheme. For the deterministic model, the scheme is third‐order accurate. The consistency and stability of the constructed scheme are provided in the mean square sense. The scheme is the predictor–corrector type that is built on two time levels. Moreover, a mathematical model of the Casson nanofluid flow with variable thermal conductivity is given with the effect of the chemical reaction. The appropriate transformations are used to condense the set of partial differential equations (PDEs) down to one that is dimensionless. The scheme is applied for the deterministic and stochastic models of dimensionless flow problems. The velocity profile's deterministic and stochastic behavior are shown using contour plots. Results show that growing values of the thermal mixed convection parameter enhance the velocity profile. This article presents the progress made in stochastic computational fluid dynamics (SCFD) and highlights the energy‐related aspects of our discoveries. Our computational approach and stochastic modeling techniques provide new insights into the energy properties of Casson nanofluid flow, specifically regarding the variability of thermal conductivity and chemical processes. Our objective is to clarify the complex interaction of these factors on energy dynamics. This article presents a contemporary summary of the latest SCFD advancements. Additionally, it highlights potential directions for future research and unresolved issues that require attention from the members of the field of computational mathematics.
Managing climate change challenges to water security: Community water governance in Ethiopia and Nepal
Authors: Flint Adrian , Howard Guy , Nijhawan Anisha , Poudel Moti , Geremew Abraham , Mulugeta Yohannes , Lo Eunice , Ghimire Anish , Baidya Manish , Sharma Subodh 
Published: February 2024

AbstractClimate change poses a threat to water security where both current and future generations are concerned, with its accompanying impacts set to be greater in low‐ and middle‐income countries (LMICs). As a result, questions pertaining to climate change adaption in LMICs are receiving increased attention from academics and policymakers alike. It is broadly accepted that top‐down approaches to developing resilience to climate change challenges have been shown to be limited and that concerted efforts need to be made to engage local communities in advancing adaptive strategies. Based on the above, we make two main arguments: (1) while there has been a shift towards acknowledging the importance of community‐driven data in generating a broader and deeper understanding of climate change, far better use could be made of local knowledge and (2) efforts at community‐based solutions to problems of resilience are currently limited by issues of capacity, specifically linked to the need for further education and training, and improved representation with respect to gender, class and caste (as well as financial support). To illustrate these arguments, we present evidence provided by rural communities located in two countries affected heavily by climate change: Ethiopia and Nepal.
Bolstering health systems to cope with the impacts of climate change events: A review of the evidence on workforce planning, upskilling, and capacity building
Authors: Zurynski Yvonne , Fisher Georgia , Wijekulasuriya Shalini , Leask Elle , Dharmayani Putu Novi Arfirsta , Ellis Louise A. , Smith Carolynn L. , Braithwaite Jeffrey 
Published: February 2024

AbstractBackgroundAs global CO2 emissions continue to rise and the ‘era of global boiling’ takes hold, the health workforce must cope with the challenge of providing care to increasing numbers of patients affected by climate change‐related events (e.g., hurricanes, wildfires, floods). In this review, we describe the impacts of these events on the health workforce, and strategies responding to these challenges.MethodsThis rapid systematic review was guided by the Preferred Reporting Items for Systematic reviews and Meta‐Analyses and a registered protocol (PROSPERO CRD42023433610). Eight databases were searched in May 2022 and again in June 2023. Empirical studies discussing climate change and workforce policy, planning, preparedness, and capacity were included. Inductive thematic analysis of extracted data was conducted.ResultsFrom the 60 included studies, two categories emerged: the impacts of climate events on the health workforce (n = 39), and workforce responses to and preparations for climate events (n = 58). Thirty‐seven studies reported on both categories. Four impact themes were identified: absenteeism, psychological impacts, system breakdown, and unsafe working conditions; and six responses and preparations themes: training/skill development, workforce capacity planning, interdisciplinary collaboration, role flexibility, role incentivisation, and psychological support.ConclusionThis review provides an overview of some of the deleterious impacts of climate events on the health workforce, as well as potential strategies for the health workforce to prepare or respond to climate events. Future studies should assess the implementation and effectiveness of these strategies to ensure a continuously improving healthcare system, and a well‐supported health workforce.
RETRACTED: Identifying baseflow source areas using remotely sensed and ground‐based hydrologic data
Authors: Ahamed Aakash , Knight Rosemary , Alam Sarfaraz 
Published: February 2024

AbstractUnderstanding how rainfall and snowmelt influence baseflow, the groundwater‐fed component of streamflow, is essential for sound water resources management. Current approaches to understand the spatial couplings between these processes and baseflow are limited. The most commonly used methods include geochemical tracers and hydrologic models. A key limitation of the first is cost, while the second is limited by the need for simplifying assumptions. This study developed a data‐driven approach which leverages satellite Earth observation data and ground‐based data to assess the degree to which baseflow is influenced by upstream rainfall and snowmelt in California's Sierra Nevada. The procedure involved: (1) separation of baseflow from streamflow time series using a low‐pass filtering technique, (2) quantification of aquifer drainage timescales through baseflow recession analysis, (3) application of time series and information theory methods to identify the areas which have the greatest impacts on baseflow through both rainfall and snowmelt, and (4) characterization of the elevation zones which have a prevailing influence on baseflow. Results suggest that areas which have the strongest impact on baseflow through rainfall and snowmelt are not necessarily the areas which experience the highest annual rates of snowmelt or rainfall; snowmelt occurring in the 3000–3700 m elevation range was found to be the most important driver of baseflow.
Water isotopic composition traces source and dynamics of water supply in a semi‐arid agricultural landscape
Authors: Mayernik Caitlin M. , Ewing Stephanie A. , Sigler W. Adam , Jencso Kelsey G. , Payn Robert A. 
Published: February 2024

AbstractChanges in seasonality and form of precipitation alter the structure and function of grassland and steppe ecosystems and pose challenges for land management and crop production in regions like the Northern Great Plains, North America. This research uses isotopic composition of water (δ18O and δ2H) to explore the sources and fate of soil water in lower‐elevation agricultural areas of the Judith River watershed, in the headwaters of the Missouri River, USA. Extensive non‐irrigated cereal crop production in this area occurs on well‐drained soils and depends on careful water management. Our observations indicate that colder precipitation contributes isotopically distinct water to cultivated terrace soils relative to downgradient groundwaters and streams. Riparian waters also exhibit a higher fraction of contributions from colder precipitation relative to terrace groundwaters and streams. Apparent contributions from colder precipitation in terrace and riparian soil waters suggest that snowmelt is a key component of the water supply to these systems. Riparian waters also show evidence of evaporation suggesting that water spends sufficient time in some ponds and open channels in the riparian corridor to reflect fractionation by evaporation. The evolution of water isotopic composition from soils to shallow aquifers to stream corridors indicates source water partitioning as precipitation moves through this semi‐arid agricultural landscape. The apparent mixing processes evident in this evolution reveal source water dynamics that are necessary to understand plant transpiration, solute processing, and contaminant leaching processes.