bluuebunny/crossref_metadata_2025 huggingface dataset:
Advanced nanomaterials for electrochemical sensors: application in wearable tear glucose sensing technology
Authors: Zhou Yue , Li Lei , Tong Jiale , Chen Xiaoli , Deng Wei , Chen Zhiyu , Xiao Xuanyu , Yin Yong , Zhou Qingsong , Gao Yongli , Hu Xuefeng , Wang Yunbing
Published: June 2024

The recent applications of nanomaterials in tear fluid electrochemical bio-glucose sensors are systematically reviewed. The challenges, strategies, and prospects for those bio-glucose sensor nanomaterials are also emphasized.
Orbital variability of polarized X-ray radiation reflected from a companion star in X-ray binaries
Authors: Ahlberg Varpu , Kravtsov Vadim , Poutanen Juri
Published: June 2024

The reflection of X-ray radiation produced near a compact object from its stellar companion contributes to the orbital variability of polarization in X-ray binaries. The X-rays are reflected mainly via Thomson scattering resulting in a high polarization. The orbital variability of the polarization strongly depends on the inclination and the orbital parameters allowing us to constrain them. To explore this phenomenon, we present analytical single-scattering models for the polarized reflection. We find that while diluted by the direct emission, the reflection can produce a polarization degree of about 1% in the case of a large reflection albedo. We fitted the orbital variations of the X-ray polarization observed by the Imaging X-ray Polarimetry Explorer from an accreting weakly magnetized neutron star “clocked burster” GS 1826−238 and found that the amplitude of the variations is too large to be primarily caused by the companion star. The polarized reflection is more significant if the compact object is obscured from the observer, and thus it should be more easily observable in certain high-inclination targets.
Convolutional neural networks for the crack diagnostics in concrete structures
Authors: Danishevskyy Vladyslav , Gaidar Anastasia , Markert Bernd
Published: June 2024

New models of artificial neural networks are proposed for the identification and classification of cracks in concrete and reinforced concrete walls. The cloud tool Teachable Machine is used to develop a neural network with a pre-defined internal architecture. TensorFlow libraries allow us to develop a convolutional neural network with a tuneable architecture. The program code is written in Python and the learning was performed using the cloud environment Colab. The rational magnitudes of the learning parameters and the topology of the convolutional neural network are determined allowing to achieve the highest accuracy and the lowest losses of the model. The obtained results show a high efficiency of the artificial intelligence to solve problems of the health monitoring of building structures. The proposed models allow real-time automatic diagnostics by analysing photographs, images from smartphone or quadcopter webcams. The latter makes it possible to inspect buildings without the physical presence of humans at the site, which is especially important for working in dangerous places, such as tall buildings, partially destroyed buildings, mined areas, etc. The proposed methods can be further extended for the monitoring and classification of a wide range of defects in building structures.
Evaluation of quality classification and comfort of the territory of urban ecosystems in terms of “Environmental conditions”
Authors: Hilov Volodymyr , Sankov Petro , Tymoshenko Olena , Poltoratska Victoria , Prokofieva Halyna
Published: June 2024

This paper considers an evaluation of environmental conditions on the territory of urban ecosystems. The research was conducted within Jean Monnet Module project 101085133 – EUGREEN, which is co-funded by the European Union. The evaluation of environmental conditions is considered as a constituent part of the integral estimation of many factors affecting the population health. In urban planning, the assessment of climate and environmental conditions is one of the stages of determining the indicator of the quality and safety of life activities of the city population. To assess the quality of life of the population according to the “Environmental conditions” indicators, it is suggested to use bioclimatic characteristics, which are effective indicators of the thermal structure of the environment of human life, especially in conditions of climate change. The purpose of the study is to determine a qualitative assessment of the environmental conditions of various urban areas of Ukraine, as a certain background against which other functions of the city are performed, as well as for their further use to ensure comfortable microclimatic conditions in residential areas.
The effect of external radiation exposure per person depending on his position and anthropometric indicators
Authors: Pylypenko Oleksandr , Shalomov Volodymyr , Strezhekurov Yurii , Rudenko Viacheslav , Tymchenko Pavlo
Published: June 2024

This study reviews existing methods for modelling the impact of ionising radiation sources on the human body. Using advanced modelling methods, the main modelling parameters are determined and it is revealed whether anthropometry affects the increase or decrease of the total radiation dose in the conditions of work in radiation-contaminated areas of the nuclear fuel cycle. The most rational and safe approach today is to conduct experimental studies on anthropomorphic mannequins to simulate human exposure using the RANDO phantom model with different geometries of exposure to ionising radiation sources. The considered modelling methods are taken from medicine, nuclear power, economics and labour protection, where they have found their application and continue to be improved. For further research, it is necessary to use other types of models, such as the Event Tree model, SWOT analysis model, Zero Risk model, Correlation and Regression System model, Matrix model, and other computer models and simulations using artificial intelligence. The factors proposed in this article provide a “complete picture” of the factors that occur in real conditions of research, measurements, service, security and physical protection of radiation-hazardous facilities such as tailing ponds of former uranium production.
Peculiarities of organizational and technological approaches to the post-war restoration of infrastructural objects in Ukraine
Authors: Savytskyi Mykola , Radkevych Anatolyi , Savytskyi Oleksandr , Babenko Maryna , Shevchenko Tetyana
Published: June 2024

As a result of russia’s insidious war against Ukraine, thousands of infrastructure facilities and energetical objects were destroyed or damaged. We are sure, Ukraine will win this war. Already today, the territories of the country freed from the occupiers with the destruction of residential and civilian buildings, infrastructure facilities need restoration. In Ukraine, the Government Plan for the Recovery of Ukraine has been developed. Ukraine’s Recovery Plan is aimed at accelerating sustainable economic growth. But this Program outlines general approaches and directions for the recovery and development of Ukraine. Therefore, it is necessary to develop detailed local programs that contain organizational and technological approaches to the implementation of restoration works. The programs must to help local authorities, territorial communities in which housing and social infrastructure objects were damaged or destroyed as a result of russian armed aggression, to make decisions regarding the planning and implementation of restoration works and the development of territories. Purpose of the study: to develop detailed Local Program which specifies the National Programs of the Recovery Plan of Ukraine and contain organizational and technological approaches to the implementation of restoration works.
Implementation of smart building management systems for residential complex “PANORAMA”
Authors: Savytskyi Oleksandr , Spyrydonenkov Vitalii , Tsyhankova Svitlana , Babenko Maryna
Published: June 2024

The European Union (EU) and Ukraine, which is following a precise European integration course, have a priority to improve energy efficiency in order to prevent negative environmental impact and achieve climate neutrality. It is known that more than 40% of the energy produced is accounted for by energy consumption in existing buildings. Analysis of energy consumption reveals a high percentage of energy losses due to poor management, which necessitates the development and implementation of systems and tools for improved energy management. Therefore, the development of energy efficient building management systems using modern engineering and technical solutions to control and optimise energy consumption is a relevant and promising way to solve the issue of energy resources saving, increase energy efficiency and enhance energy independence. Within the framework of the international research grant “A novel decentralized edge-enabled PREsCriptivE and ProacTive framework for increased energy efficiency and well-being in residential buildings” – PRECEPT under the Horizon 2020 programme, smart building management system was developed and implemented at the residential complex “PANORAMA” in Dnipro city, Ukraine.
Information modeling of the foundation of a special-purpose industrial building
Authors: Sedin Volodymyr , Zahilsky Vitaliy , Tytiuk Andrii , Kovba Vladyslav , Vershkova Yuliia
Published: June 2024

The paper considers the peculiarities of construction of special structures based on individual projects and requiring non-standard approaches to design and calculation due to unique loads and impacts on the structure. The author emphasizes the importance of transferring design to the field of virtual building information model (BIM) to ensure a high level of detail, accurate calculation of materials and works, as well as the possibility of making changes to the BIM model for further monitoring of the life cycle of the structure. It is noted that the use of BIM programs allows to effectively take into account all components of the structure and minimizes technical errors in the coordination of engineering networks with structural drawings. The purpose of this paper is to analyze the results of building design using computer-aided design (CAD) and building information modeling (BIM) systems. The work is aimed at studying the efficiency and accuracy of the design performed using CAD technologies and comparing it with the results obtained through the use of BIM modeling. Changes that occur to the building and are not foreseen in the original design can be incorporated into the model, which ensures that the information is upto-date and relevant throughout the entire life cycle of the building.
Does the cost of environmental regulation affect the development of the green economy? ——A quasi natural experiment on changing environmental protection fees to taxes in China
Authors: Dong Bingrui , Li Meihong , Liu Dangwen , Chen Xiuxiu , Xie Bangsheng
Published: June 2024

Environmental regulation is a crucial mechanism for attaining both environmental preservation and sustainable development. So, how does the changes in regulatory costs affect the development of green economy? We use Difference-in-Differences model to test the impact of environmental tax implementation on the level of green economy in 30 provinces, municipalities, and autonomous regions of China from 2011 to 2020.Our research find that the implementation of environmental protection tax effectively improve the level of green economy in the areas where the tax burden was raised, that is, the increase in the cost of environmental regulation would promote the growth of the level of green economy. Through a series of robustness tests such as outlier test, placebo test, reduced sample test, lagging independent variable, and control variable, the conclusions of this paper are still robust. Further analysis reveals that the implementation of environmental protection taxes has significantly improved the level of green innovation, industrial structure, and energy use efficiency in tax bearing areas. Heterogeneity analysis find that the impact of environmental protection tax implementation on regional green economy mainly occurs in the tax burden increase areas in the central and western regions. In places characterized by elevated levels of green credit and tax burden, the introduction of environmental protection levies exhibits a more pronounced impact on fostering green economic growth. Hence, it is recommended to further augment environmental rules, broaden the ambit of environmental tax collection, and strengthen regional green credit support in order to facilitate the advancement of the green economy towards high-quality development.
Mitigating Urban Heat Islands in Wuhan: The Role of Urban Parks Over the Past Five Years
Authors: She Jian
Published: June 2024

In recent years, the urban heat island effect has emerged as a significant challenge in global urban planning and environmental management. The impact of urban parks, as integral components of urban green space systems, on mitigating the heat island effect has garnered considerable attention. This paper conducts an analysis of the impact of urban parks on the urban heat island effect in Wuhan over the past five years, systematically exploring the mechanisms and effects of urban parks on the heat island effect. The study reveals that with the increase in total area of urban parks, their cooling effect becomes progressively more pronounced. Park area, perimeter, and vegetation coverage are all negatively correlated with surface temperature, exhibiting a trend of increasing influence. The perimeter-area ratio is positively correlated with surface temperature, indicating that parks with more regular shapes demonstrate better cooling effects. Urban parks exhibit better cooling effects within a radius of 100 meters from their perimeters. Currently, the cooling effects and coverage of parks are gradually expanding.
Measurement of Environmental Population Capacity Based on Island Environment–A Case Study of Hainan Island and Ireland Island in China
Authors: Chen Yijing , Zhu Yuanyuan , Lai Binyu
Published: June 2024

In this paper, the influencing factors of environmental population capacity are categorized into three types: strict constraints, elastic constraints and non-constraints, and the systematic relationship among the three types of factors is explored, from single-factor environmental population capacity model to multifactor environmental population capacity model, and finally to obtain the regional environmental population capacity model. In this paper, we choose to take Hainan Island in China and the island of Ireland, which have similar natural conditions (area, population, etc.), as examples to measure the environmental population capacity based on the island. From the perspective of environmental capacity, this paper explores how to make the global distribution of population settlements more in line with the distribution of environment and resources, and then puts forward more effective and reliable suggestions for the coordinated development of population and economic and social resources and environment.
Characteristics Analysis of CO2 Concentrations and Temperature in Residential Buildings in Severe Cold Area Based on Field Measurement
Authors: Li Guozhu , Zhang Yilin , Guo Yang , Wei Jiaxing , Zhou Haizhu , Xie Linna , Luo Bin , Zhao Naini
Published: June 2024

This paper provides references for the design and control of high-quality green building indoor environments during the transitional season in severe cold area. A residential building in severe cold area was selected as the research subject, where indoor pollutant CO2 concentrations and temperatures were measured at the beginning of the transitional season. The study explored the variations in indoor pollutant temperatures and CO2 concentrations under natural and non-natural ventilation conditions, in conjunction with an analysis of the occupants' activities. The results demonstrated clear relationships between indoor pollutant CO2 concentrations and temperatures under natural ventilation conditions. Based on these findings, recommendations for natural ventilation strategies that consider both indoor CO2 levels and thermal environment are proposed.
Research on Global Climate Change Prediction based on Machine Learning Model
Authors: Lv Yunhang , Tan Yunxiang , Zeng Yuanjun , Wang Kai
Published: June 2024

Climate prediction models have traditionally relied on complex physical equations to simulate the dynamics of the climate system, but these models often require significant computational resources and long computational lengths. In recent years, machine learning techniques have shown great potential for pattern recognition and prediction. Specifically, machine learning models have become a hot research direction in the field of climate science due to their advantages in processing large-scale datasets. In this work, we propose a convolutional neural network-based (CNN) model capable of processing and analysing large-scale climate datasets from satellites, including multi-dimensional data including temperature, air pressure, humidity, and CO2 concentration. The input is historical climate data, and the spatial features are extracted through the convolutional layer, and then the feature fusion and final prediction output are performed through the fully connected layer. Finally, we utilized historical climate data as the training set and tested the model on data over multiple time periods. The results show that compared with traditional physical models, CNN-based models provide higher accuracy and lower prediction errors in predicting global average temperature changes, precipitation, and extreme weather events.
Virtual screening of potential biofungicide candidate for sustainable fungal disease control
Authors: Yongpisanphop Jiraporn
Published: June 2024

Captafol is widely used as a fungicide compound. However, it is banned in Thailand due to its carcinogen risk level. This study aimed to search for a potential biofungicide candidate via a computational approach to compensate the using of chemical fungicide. Based on the goal, natural compounds showing structures and properties similar to those of captafol were retrieved from various databases. The fungicide-likeness properties were screened. The binding pocket of chitin synthase I was identified, after which virtual screening was performed by AutoDock Vina, and interaction patterns were analysed by Discovery Studio. Finally, kaurane-16,18-diol 18-acetate (NPC132839) extracted from plants was selected as a potential biofungicide candidate with -7.0 kcal/mol of binding energy. The outcomes of this study could be utilised as a highly useful resource to increase the successful exposure of bioactive compounds of plant extracts without damage the environment.
Removal of o-Nitrophenol via Adsorption by Porous Carbon Derived from Magnesium Oxide and Waste Polyethylene Terephthalate Prepared by Template Method
Authors: Shen Yahao , Ding Junwei
Published: June 2024

In the present paper, the porous carbon material derived from waste PET was fabricated using a one-step recyclable MgO template synthesis approach. The material was subsequently employed as adsorbent for the efficient capture of o-nitrophenol (ONP) from aqueous solutions. With the change of the ratio of MgO template to waste PET, the prepared porous carbon has controllable specific surface area. The sample of WPC-1.5 exhibits a remarkable specific surface area of 885.99 m2/g. Static adsorption experiments demonstrate that this material possesses a substantial adsorption capacity for ONP, achieving a value of 474 mg/g. The WPC-1.5 was characterized by scanning electron microscopy, BET and adsorption kinetic and equilibrium isotherms evaluation.
Effects of microplastics on granular sludge: A review
Authors: Tan Chang , Wang Qian , Li Fengmin
Published: June 2024

Biogranules are recently regarded as promising methods with intensive density and satisfying settleability for waste treatment and resource recovery. Wastewater treatment plants (WWTP) were regarded as “sinks” for Microplastics (MPs) and amount of MPs entrapped in the sludge. MPs have been reported to harm the granular characteristics and wastewater treatment efficiency. Previous research stated that the harmful effect on granular sludge is closely associated with the sizes and concentrations of MPs. However, there is still a lack of a comprehensive summary of granular characteristics variation and further investigation of its influential mechanisms for treatment capability. This work gives informative clues for the regulation mechanisms, especially the microorganisms’ response after the exposure of MPs, and provides fundamentals for stable operation and risk control strategies using granular sludge in treating microplastics containing wastewater.
Advances in volatile organic pollutant capture and adsorption degradation treatment technologies
Authors: Xu Yinan , Mao Lihui , Shao Chida , Zhu Bin , Meng Fandong , Zhang Qinghua , Yu Zhipeng , Wang Junhui
Published: June 2024

With the continuous development of industry, the emission of volatile organic compounds (VOCs) continues to increase, and the pollution problem becomes increasingly serious. For example, in industrial production processes such as papermaking and traditional Chinese medicine extraction, low-content and complex volatile organic compounds will be produced, which will affect the factory environment. This article introduces the development and research status of VOCs sampling and treatment technology in recent years, explains the advantages and disadvantages of adsorption method, absorption method, membrane separation method, catalytic combustion method, biodegradation method, and low-temperature plasma technology application, and looks forward to the future development trends in this field.
Research on SO3 prediction method in thermal power plant flue gas based on machine learning
Authors: Wang Kai , Ge Tiancheng , Zhao Lei , Jiang Weiting
Published: June 2024

In order to reduce nitrogen oxides in the earth's atmosphere caused by pollution. Thermal power plants are gradually adding a selective catalytic reduction denitrification technology during the operation of the power plant. But in the power plant in the process of the denitration, the phenomenon of sulfur dioxide (SO2) being oxidized to sulfur trioxide (SO3) occurs and cannot be accurately monitored. Therefore, in order to have a more intuitive understanding of SO3 emissions from power plants, we use a transfer learning based on VGG16 network to study it, which is of significant reference value for the application of machine learning techniques in predicting atmospheric pollution from thermal power plants. Real smoke data is put into the model to make predictions, analyze and verify the effects, and compare the predicted effects with other machine learning models showing that the transfer learning model has higher identification accuracy.
Removal of hexavalent chromium using polyphenol-based functional materials
Authors: Wen Jia , Long Xingye , Fang Yingchun , Cheng Wenxing
Published: June 2024

Chromium from industrial wastewater, waste, pesticides, fertilizers, etc., always causes serious environmental problems. High levels of chromium pollution can have adverse effects on environments and living organisms. In this study, titanium salt was used to react with green tea extract to form a composite material, and the material was further used to remove hexavalent chromium in solution. The removal effect of hexavalent chromium was investigated under different reaction conditions, namely temperature, time, pH, and initial chromium concentration. The results showed that the chromium removal effect was the best under the conditions of acid to neutral pH, 45℃, reaction time of 24 h, and initial chromium concentration of 80 mg/L. This study provides a feasible method to solve the problem of chromium pollution and has high application value in wastewater treatment.
Numerical Simulation of Pollutant Channeling between Adjacent Road Tunnels
Authors: Tang Sha , Han Xiaoyang , Zhi Yansheng
Published: June 2024

With the development of highway tunnels, the increasing number of continuous tunnels has brought forth a growing concern regarding the dispersion of pollutants between tunnel entrances. This study employs numerical simulations with Star CCM+ to analyze factors influencing pollutant dispersion between continuous tunnel entrances, such as inlet and outlet velocities, longitudinal spacing, and lateral wind. Results indicate that maintaining a constant longitudinal size ratio while increasing velocity ratio augments intrusion ratio. Altering longitudinal spacing and equivalent diameter does not affect dispersion with constant velocity and size ratios. The intrusion ratio decreases with increasing longitudinal size ratio at a constant velocity ratio. Increased lateral wind weakens intrusion with constant velocities and longitudinal size ratio. This investigation aims to identify ventilation measures for mitigating pollutant dispersion impact in continuous tunnels.
Optimization of Injection Rate for CO2 Geological Storage Based on Differential Evolution
Authors: Liu Bin , Shi Chunsheng
Published: June 2024

CO2 geological storage is one of the important means to reduce carbon emission and greenhouse effect, and it is an emerging field of earth science research. The selection of the injection rate has an important impact on the CO2 storage capacity, and it is limited by the injection time and construction conditions, thus the selection of the injection rate is a complex optimization problem. In this paper, the optimal injection site calculated based on dynamic planning is used for injection simulation, based on which the carbon sequestration injection rate optimization problem is transformed into a differential evolution problem, and the problem is optimized by different differential methods. For the Utsira block in the Sleipner project in Norway. On this basis, the effect of injection rate on storage capacity and leakage is researched, and numerical simulations under different injection rates are designed. Thus, it provides theoretical guidance for the selection of injection rate in CO2 geological storage.
One step synthesis of 3D BaTiO3@C for novel electromagnetic shielding of epoxy composites
Authors: Zhang Dongmei , Yang Yongzhi , Liu Xiaoqian , Xu Runhan , Li Yuchao , Guo Wenbin , Wang Shuangshuang , Xie Qian , Liao Chengzhu
Published: June 2024

The ever-increasing electromagnetic interference (EMI) pollution becomes an important issue in current environmental protection and human society. In this work, 3D BaTiO3(3DBT)@C porous ceramic framework was one-step fabricated by sol-gel method using environmentally friendly cleanroom wipers as template and calcined under inert atmosphere. Subsequently, epoxy (EP) resin was reversely incorporated into the above 3DBT@C network, resulting in the 3DBT@C/EP composite. Results showed that the cleanroom wiper was calcined and transformed into amorphous carbon within the 3DBT, leading to the excellent electrical conductivity of 3DBT@C. The reverse infiltration of EP maintained the successive 3DBT framework and excellent conductivity, thus endowing the 3DBT@C/EP composite with a good electromagnetic interference shielding effectiveness (EMI SE) as high as 36.6 dBꞏmm-1 at 10.2 GHz. The absorption mechanism of EMI prevailed the EMI SE due to the large Ohmic loss and porous 3D network, implying potential applications in flexile shielding materials.
Effects of climate warming on the dynamics of mineral elements accumulation in Solanum tuberosum L.
Authors: Wang Xiaoheng , Zhang Fang
Published: June 2024

A simulated experiment was conducted to evaluate the effects of climate warming on the bioaccumulation, translocation and distributions of mineral elements in Solanum tuberosum L. by increasing temperature and CO2 concentration in an artificial climate greenhouse. The objective was to explore the effects of global warming on crop mineral nutrition and the long-term effects on agricultural ecology. The results showed that the bioaccumulation of Cu, Mg, Fe, Mn, and Cd in Solanum tuberosum L increased in whole plant with the combined increase of temperature and CO2 concentration. The mineral elements in leaves, stems, tubers, and root tissues of Solanum tuberosum L showed different changes, and the trend and degree of change vary depending on the element. The migration of most elements from roots to leaves and stems showed a slight increase with the increasing of temperature and the concentration of CO2, while the migration from roots to tubers remained relatively stable. In addition, the available content of most mineral elements (except K) in the soil increased with increasing temperature and CO2 concentration. These results suggested that climate warming could change the bioaccumulation, migration, and distribution dynamics of mineral elements in Solanum tuberosum L.
The design of the dust suppression system in sand sorting process
Authors: Li Yanxia , Fan Chengzhou , Liu Zhenxing , Bi Yongdong , Li Shiguo
Published: June 2024

The sand separation process will produce a lot of dust, which will cause serious harm to the environment and personnel. Only by adopting a suitable dust removal system structure can the expected dust removal effect be obtained. In this experiment, two sets of dust suppression system, namely negative pressure dust suppression system and water mist dust suppression system, were designed and manufactured. The dust suppression effect was tested under the conditions of different air volume, air inlet hood distance and water pressure/water volume. The experimental results show that: (1). Compared with the water mist dust suppression system, the negative pressure dust suppression system has a better dust suppression effect. After the dust suppression system is turned on, the dust concentration measured within 0.2 meters around the sorting area does not exceed 6.9 mg/m3; (2). The air inlet volume of the negative pressure dust suppression system is recommended to be 1000 m3/h~1300 m3/h, and the distance between the air inlet hood and the dust initiation point is recommended to be no more than 2.5 cm. (3). The water mist dust suppression system can reduce the dust concentration to about 12mg/m3, however, there are some problems, such as slow response of dust suppression system, mud attached to the conveyor belt and affecting the transmission. The results can provide reference for the detailed design of the dust removal system.
L’asymétrie faciale, quelles origines ? la prise en charge ostéopathique
Authors: Lalauze-Pol Roselyne
Published: June 2024

L’asymétrie faciale (AF) ne semble pas être une fatalité quand elle n’est pas liée à une dysmorphose faciale d’origine syndromique. L’AF est, le plus souvent, la conséquence, des contraintes subies in utero et/ou pendant la parturition, voire des déformations crâniennes positionnelles acquises durant les premiers trimestres de vie. Le dépistage de l’AF est essentiel, et ses mesures initiales sont indispensables pour mesurer l’efficacité du traitement pour la réduire. Cet article expose divers cas cliniques infantiles, à divers âges, et la possibilité de leur prise en charge par un traitement ostéopathique pédiatrique dès les premières années et, plus tardivement par un traitement conjoint avec l’orthodontiste. Les résultats exposés semblent liés à l’action mécanotransductrice du traitement proposé.
Revisiting DFT+U calculations of TiO2 and the effect of the local-projection size
Authors: Park Kenneth , Raman Manjula , Olatunbosun Anjy-Joe , Pohlmann Jared
Published: June 2024

The method of density functional theory (DFT) combined with Hubbard U correction has been employed in wide-ranging applications in correlated systems. Although the DFT+U method can dramatically improve the treatment of many strongly correlated systems, careful attention must be paid to those parameters that significantly influence results. By varying the local-projection size with the muffin-tin radius, we examine the effect of the Hubbard U correction on lattice parameters, electronic structure, and the relative stability of TiO2 between rutile and anatase. Our results show that different ranges of the local projection can produce strikingly different quantitative results, leading to distinct conclusions. The quantitative discrepancies are attributed to the sensitivity of the occupancy numbers for the correlated orbitals toward the size of the projection subspace.
Meta-analysis and public policy: Reconciling the evidence on deworming
Authors: Croke Kevin , Hamory Joan , Hsu Eric , Kremer Michael , Maertens Ricardo , Miguel Edward , Więcek Witold
Published: June 2024

The WHO recommends mass drug administration (MDA) for intestinal worm infections in areas with over 20% infection prevalence. Recent Cochrane meta-analyses endorse treatment of infected individuals but recommend against MDA. We conducted a theory-agnostic random-effects meta-analysis of the effect of multiple-dose MDA and a cost-effectiveness analysis. We estimate significant effects of MDA on child weight (0.15 kg, 95% CI: 0.07, 0.24;
P
< 0.001), mid-upper arm circumference (0.20 cm, 95% CI: 0.03, 0.37;
P
= 0.02), and height (0.09 cm, 95% CI: 0.01, 0.16;
P
= 0.02) when prevalence is over 20% but not on Hb (0.06 g/dL, 95% CI: −0.01, 0.14;
P
= 0.1). These results suggest that MDA is a cost-effective intervention, particularly in the settings where it is recommended by the WHO.
Inhibition of a cyclic nucleotide-gated channel on neuronal cilia activates unfolded protein response in intestinal cells to promote longevity
Authors: Li Dongdong , Chen Di , Li Wei , Ou Guangshuo
Published: June 2024

Ciliary defects are linked to ciliopathies, but impairments in the sensory cilia of
Caenorhabditis elegans
neurons extend lifespan, a phenomenon with previously unclear mechanisms. Our study reveals that neuronal cilia defects trigger the unfolded protein response of the endoplasmic reticulum (UPR
ER
) within intestinal cells, a process dependent on the insulin/insulin-like growth factor 1 (IGF-1) signaling transcription factor and the release of neuronal signaling molecules. While inhibiting UPR
ER
doesn’t alter the lifespan of wild-type worms, it normalizes the extended lifespan of ciliary mutants. Notably, deactivating the cyclic nucleotide-gated (CNG) channel TAX-4 on the ciliary membrane promotes lifespan extension through a UPR
ER
-dependent mechanism. Conversely, constitutive activation of TAX-4 attenuates intestinal UPR
ER
in ciliary mutants. Administering a CNG channel blocker to worm larvae activates intestinal UPR
ER
and increases adult longevity. These findings suggest that ciliary dysfunction in sensory neurons triggers intestinal UPR
ER
, contributing to lifespan extension and implying that transiently inhibiting ciliary channel activity may effectively prolong lifespan.
Chapter 32. Between history and fiction
Authors: Westenholz Willum
Published: June 2024

This piece explores some of the devices used by Medieval historiographers to assure their audience of the veracity of the contents of their narratives. It outlines central Medieval concepts of truth, lies, and fiction, the marvelous and the wondrous, and the standards for historicity and for credibility. The article highlights the pains the authors took to ensure that the readers placed their belief in what was told to them. This leads to a final question. Could the same strategies that were employed to establish a contract of veridiction be employed to establish a much more limited form of narrative truth, the suspension of disbelief? As is shown, these strategies are found in some truly incredible texts.
A machine learning ensemble approach for predicting solar-sensitive hybrid photocatalysts on hydrogen evolution
Authors: Bakır Rezan , Orak Ceren , Yüksel Aslı
Published: June 2024

Hydrogen, as the lightest and most abundant element in the universe, has emerged as a pivotal player in the quest for sustainable energy solutions. Its remarkable properties, such as high energy density and zero emissions upon combustion, make it a promising candidate for addressing the pressing challenges of climate change and transitioning towards a clean and renewable energy future. In an effort to improve efficiency and reduce experimental costs, we adopted machine learning techniques in this study. Our focus turned to predictive analyses of hydrogen evolution values using three photocatalysts, namely, graphene-supported LaFeO3 (GLFO), graphene-supported LaRuO3 (GLRO), and graphene-supported BiFeO3 (GBFO), examining their correlation with varying levels of pH, catalyst amount, and H2O2 concentration. To achieve this, a diverse range of machine learning models are used, including Random Forest (RF), Decision Tree (DT), Support Vector Machine (SVM), XGBoost, Gradient Boosting, and AdaBoost—each bringing its strengths to the predictive modeling arena. An important step involved combining the most effective models—Random Forests, Gradient Boosting, and XGBoost—into an ensemble model. This collaborative approach aimed to leverage their collective strengths and improve overall predictability. The ensemble model emerged as a powerful tool for understanding photocatalytic hydrogen evolution. Standard metrics were employed to assess the performance of our ensemble prediction model, encompassing R squared, Root Mean Squared Error (RMSE), Mean Squared Error (MSE), and Mean Absolute Error (MAE). The yielded results showcase exceptional accuracy, with R squared values of 96.9%, 99.3%, and 98% for GLFO, GBFO, and GLRO, respectively. Moreover, our model demonstrates minimal error rates across all metrics, underscoring its robust predictive capabilities and highlighting its efficacy in accurately forecasting the intricate relationships between GLFO, GBFO, and GLRO values and their influencing factors.
Predictive analytics of wear performance in high entropy alloy coatings through machine learning
Authors: Sivaraman S , Radhika N
Published: June 2024

High-entropy alloys (HEAs) are increasingly renowned for their distinct microstructural compositions and exceptional properties. These HEAs are employed for surface modification as coatings exhibit phenomenal mechanical characteristics including wear and corrosion resistance which are extensively utilized in various industrial applications. However, assessing the wear behaviour of the HEA coatings through conventional methods remains challenging and time-consuming due to the complexity of the HEA structures. In this study, a novel methodology has been proposed for predicting the wear behaviour of HEA coatings using Machine Learning (ML) algorithms such as Support Vector Machine (SVM), Linear Regression (LR), Gaussian Process Regression (GPR), Least Absolute Shrinkage and Selection Operator (LASSO), Bagging Regression (BR), Gradient Boosting Regression Tree (GBRT), and Robust regressions (RR). The analysis integrates of 75 combinations of HEA coatings with processing parameters and wear test results from peer-reviewed journals for model training and validation. Among the ML models utilized, the GBRT model was found to be more effective in predicting wear rate and Coefficient of Friction (COF) with the highest correlation coefficient of R2 value of 0.95 ∼ 0.97 with minimal errors. The optimum model is used to predict the unknown wear properties of HEA coatings from the conducted experiments and validate the results, making ML a crucial resource for engineers in the materials sector.
Effect of heat treatment on microstructure and mechanical properties of AG728 steel joints welded with ER90S-G wires
Authors: Feng Yizheng , Xu Xiangping , Wang Xiling , Wang Lingyu , Zou Jiasheng , Wang Ziqing
Published: June 2024

This study utilised self-developed ER90S-G wires for butt welding tests on AG728 plates to investigate the influence of heat treatment on the microstructure and mechanical properties of welded joints. Furthermore, it aimed to analyse the microstructure and metallurgical mechanisms of these joints. The findings reveal that the microstructure of the welded joints primarily consists of acicular ferrite with a minor presence of granular bainite. Following heat treatment, there is a noticeable growth in acicular ferrite and the emergence of tempered sorbite and massive ferrite; concurrently, austenite grain boundaries vanish, carbide aggregation increases, the quantity of large angular grain boundaries diminishes, and the martensite–austenite constituent elements gradually disappear. The physical phase of the base material, the heat-affected zone (HAZ), and the welded joints uniformly transition to α-Fe. Additionally, inclusions measuring 0.5 μm, predominantly MnSiO3, evidently promote the formation of ferrite. The tensile strength and impact toughness experience a minor reduction while the hardness of the HAZ and weld seam significantly decreases. The micro-morphology of the welded joint’s tensile fracture is predominantly characterised by dimples, within which inclusions or precipitated phase particles are distinctly visible, indicating a microporous coalescence-type fracture. At −45 °C, the impact test of welded joints reveals that the HAZ impact fracture micro-morphology exhibits brittle deconstructive fracture patterns, which, through heat treatment, transition to quasi-cleavage characteristics with reduced and shorter river patterns. The base material and weld fracture micro-morphology are primarily defined by the presence of dimples.
Entangled multiplets, asymmetry, and quantum Mpemba effect in dissipative systems
Authors: Caceffo Fabio , Murciano Sara , Alba Vincenzo
Published: June 2024

Recently, the entanglement asymmetry emerged as an informative tool to understand dynamical symmetry restoration in out-of-equilibrium quantum many-body systems after a quantum quench. For integrable systems the asymmetry can be understood in the space-time scaling limit via the quasiparticle picture, as it was pointed out in Areset al(2023Nat. Commun.142036) . However, a quasiparticle picture for quantum quenches from generic initial states was still lacking. Here we conjecture a full-fledged quasiparticle picture for the charged moments of the reduced density matrix, which are the main ingredients to construct the asymmetry. Our formula works for quenches producing entangled multiplets of an arbitrary number of excitations. We benchmark our results in theXXspin chain. First, by using an elementary approach based on the multidimensional stationary phase approximation we provide anab initiorigorous derivation of the dynamics of the charged moments for the quench treated in Areset al(2023SciPost Phys.15089). Then, we show that the same results can be straightforwardly obtained within our quasiparticle picture. As a byproduct of our analysis, we obtain a general criterion ensuring a vanishing entanglement asymmetry at long times. Next, by using the Lindblad master equation, we study the effect of gain and loss dissipation on the entanglement asymmetry. Specifically, we investigate the fate of the so-called quantum Mpemba effect (QME) in the presence of dissipation. We show that dissipation can induce QME even if unitary dynamics does not show it, and we provide a quasiparticle-based interpretation of the condition for the QME.
Entanglement Hamiltonian in the non-Hermitian SSH model
Authors: Rottoli Federico , Fossati Michele , Calabrese Pasquale
Published: June 2024

Entanglement Hamiltonians provide the most comprehensive characterisation of entanglement in extended quantum systems. A key result in unitary quantum field theories is the Bisognano-Wichmann theorem, which establishes the locality of the entanglement Hamiltonian. In this work, our focus is on the non-Hermitian Su-Schrieffer-Heeger (SSH) chain. We study the entanglement Hamiltonian both in a gapped phase and at criticality. In the gapped phase we find that the lattice entanglement Hamiltonian is compatible with a lattice Bisognano-Wichmann result, with an entanglement temperature linear in the lattice index. At the critical point, we identify a new imaginary chemical potential term absent in unitary models. This operator is responsible for the negative entanglement entropy observed in the non-Hermitian SSH chain at criticality.
Mathematical model of explosion-proof performance of pressure container packaging based on dimension analysis
Authors: Wen Quan , Zhu Jiale , Mi Chenxi
Published: June 2024

As the protective body of the pressure container, the reliability of pressure container packaging directly determines the safety of the pressure container. Therefore, the explosion-proof performance of pressure container packaging is crucial. In order to measure the explosion-proof performance of pressure container packaging, witness plate pressure is used to measure the explosion-proof performance of pressure container packaging, and a method based on dimension analysis is proposed to establish a mathematical model of the explosion-proof performance of pressure container packaging. This model quantitatively solves the nonlinear relationship between the peak pressure of the witness plate and the number of pressure container packaging layers, pressure container packaging thickness, and packaging materials. Applying this to the design of pressure container packaging can provide a reference for improving the explosion-proof performance of pressure container packaging.
Experimental study on strength and carbonation performance of hybrid fibre lightweight aggregate concrete in precast structures
Authors: Zhao Xiaolang , Zheng Xiuhua , Zhong Wei , Jiang Wei , Hu Dingyu
Published: June 2024

To improve the brittle failure characteristics and carbonation performance of lightweight aggregate concrete, basalt fibre, and polyacrylonitrile fibre were incorporated. The effects of the two fibres on the compression strength and carbonation depth were studied through compression tests and rapid carbonation tests. The effects of mineral admixture proportion were also studied. The results show that when the mass content of basalt fibre and polyacrylonitrile fibre is 2.8 kg/m3 and 0.9 kg/m3, respectively, the average increase of compression strength for different ages is approximately 40%, and the average decrease of carbonation depth for different ages is approximately 8%. Furthermore, when the mass content of mineral admixture is 30%, the higher proportion of slag contributed to the greater compression strength, but smaller carbonation depth. As supported by the experimental results, the improvements in strength and carbonation performance of lightweight aggregate concrete will make it more competitive in the application of precast buildings and long-span bridges.
Composite manufacturing of metal porous thin strip with metal wire mesh and powder
Authors: Lin Shengcun , Feng Wenxiu , Shi Fusheng
Published: June 2024

Porous metal materials are applied in various industries, among which powder rolling is the most widely used process for preparing porous metal materials. Then, metal porous materials prepared solely from powder as raw materials have the disadvantage of low mechanical properties, while wire mesh as reinforcement can effectively improve tensile strength. The preparation process of wire mesh powder composite is complex and requires the addition of adhesives. In this article, the mechanical properties of thin metal strips prepared by powder and wire mesh composite vertical rolling were much higher than those prepared by pure powder. Moreover, this thin strip had porous characteristics, and the preparation process was simple and easy to promote. This research could provide a reference for the powder metallurgy field, especially for the preparation of metal porous materials by vertical rolling.