bluuebunny/crossref_metadata_2025 huggingface dataset:
“Rally around the flag” effects in the Russian–Ukrainian war
Authors: Kizilova Kseniya , Norris Pippa
Published: November 2023

Following Russia’s full-scale invasion of Ukraine on February 24, 2022, the grounds behind Vladimir Putin’s decision were widely debated. Theories suggest several reasons, including Putin’s nostalgic dream of restoring Soviet imperial glory, Russia’s fears of NATO security threats near their borders. But another explanation may be more prosaic: Putin’s desire to restore his sagging popularity at home by attempting to repeat his 2014 “Crimea” strategy. By annexing territories in Eastern Ukraine, he may have hoped to generate a “rally-around-the flag” effect, boosting his domestic support by appealing to Russian patriotism and nationalism. To examine this thesis, Part I outlines the core concept and what is known in the literature about the size and duration of the rally-around-the flag phenomenon. Part II examines the available time-series survey evidence drawn from a variety of opinion polls in Ukraine, Europe, and Russia focusing on the first 8 months of the war to detect any rally effects associated with Russia’s invasion of Ukraine. Part III examines the evidence of media effects. Part IV adds robustness tests. The conclusion in Part V summarizes the main findings and discusses their broader implications for understanding the roots of the Russian invasion of Ukraine and its consequences.
Social policy in a future of degrowth? Challenges for decommodification, commoning and public support
Authors: Kongshøj Kristian
Published: November 2023

Achieving sustainability within planetary boundaries requires radical changes to production and consumption beyond technology- and efficiency-oriented solutions, especially in affluent countries. The literature on degrowth offers visions and policy paths with the explicit aim of ensuring human wellbeing within an economy with a lower resource metabolism. This paper reviews and discusses the academic literature on degrowth with the aim of deriving the main inherent challenges where further research is needed. Proponents of degrowth envisage radical redistribution and decommodification with ‘floors’ and ‘ceilings’ for income and wealth, as well as extensive public service provision. This paper outlines how results from other research support such a policy direction. However, the paper discusses three inherent challenges for such a future with respect to the feasibility and desirability of degrowth policies, as well as their legitimate underpinning in public support. This includes the internal growth dependencies of established social policies, which require changes to financing, output-based management and perhaps even curtailing input (service demand). Secondly, it concerns the role of public welfare provision when degrowth advocates also envisage the proliferation of alternative and informal economies. The paper emphasises that these two challenges invite more work on where public service provision should play a lesser role. Thirdly, the paper covers popular legitimacy. In affluent democracies, popular support needs to expand further beyond the ‘new left’ or the ‘green left’, even if larger shares of the population exhibit some potential for growth-critical stances. At the heart of these challenges is the need for new norms and values with respect to wellbeing, which is envisaged in the literature as a shift from materialist and hedonic towards needs-oriented and eudaimonic conceptions of wellbeing and happiness.
Connecting with fans in the digital age: an exploratory and comparative analysis of social media management in top football clubs
Authors: Romero-Jara Edgar , Solanellas Francesc , Muñoz Joshua , López-Carril Samuel
Published: November 2023

In a globalised society, characterised by increasingly demanding markets and the accelerated growth of the digital approach, sports organisations face the challenge of connecting with fans, generating and maintaining audiences and communicating with stakeholders creatively and efficiently. Social media has become a fundamental tool, with engagement as a critical measurement element. However, despite its popularity and use, many questions about its application, measurement and real potential in the sports sector still need to be answered. Therefore, the main objective of this study is to carry out a descriptive and comparative analysis of the engagement generated through social media posts by elite football clubs in Europe, South America and North America. To this purpose, 19,745 Facebook, Twitter and Instagram posts were analysed, through the design, validation and application of an observation instrument, using content analysis techniques. The findings show evidence of a priority focus on “Marketing” and “Sports” type messages in terms of frequency, with high engagement rates. They were also showing a growing stream of “ESG” type messages, with a low posting frequency but engagement rates similar to “Marketing” and “Sport”. “Institutional” messages remain constant in all football clubs. “Commercial” messages still have growth potential in both regards, frequency and engaging fans, representing an opportunity for digital assets. Also, specific format combinations that generate greater engagement were identified: “text/image” and “text/videos” are the format combinations more used by football clubs on Facebook, Twitter and Instagram; however, resulting in different engagement rates. This study showed evidence of different social media management strategies adopted according to region, obtaining similar engagement rates. This research concludes with theoretical and practical applications that will be of interest to both academics and practitioners to maximise the potential of social media for fan engagement, social initiatives and as a marketing tool.
Observations of very fast electron traps at SiC/high-κ dielectric interfaces
Authors: Vidarsson Arnar M. , Persson Axel R. , Chen Jr-Tai , Haasmann Daniel , Hassan Jawad Ul , Dimitrijev Sima , Rorsman Niklas , Darakchieva Vanya , Sveinbjörnsson Einar Ö.
Published: November 2023

Very fast interface traps have recently been suggested to be the main cause behind poor channel-carrier mobility in SiC metal–oxide–semiconductor field effect transistors. It has been hypothesized that the NI traps are defects located inside the SiO2 dielectric with energy levels close to the SiC conduction band edge and the observed conductance spectroscopy signal is a result of electron tunneling to and from these defects. Using aluminum nitride and aluminum oxide as gate dielectrics instead of SiO2, we detect NI traps at these SiC/dielectric interfaces as well. A detailed investigation of the NI trap density and behavior as a function of temperature is presented and discussed. Advanced scanning transmission electron microscopy in combination with electron energy loss spectroscopy reveals no SiO2 at the interfaces. This strongly suggests that the NI traps are related to the surface region of the SiC rather than being a property of the gate dielectric.
Temperature effect on surface structure of single crystal SrLaAlO4(001)
Authors: Mousley P. , Nicklin C. , Pramana S. S. , van den Bosch C. , Ryan M. P. , Skinner S. J.
Published: November 2023

Development of next-generation electrochemical devices, such as solid oxide cells, requires control of the charge transfer processes across key interfaces. Structural strain at electrolyte:electrode interfaces could potentially alter the devices’ charge transport properties, therefore understanding the structural behavior of electrode surfaces under operating conditions is important. The functional oxide single crystal substrate SrLaAlO4 has been well-characterized with bulk structure studies; however, there are very few studies of SrLaAlO4 surface structures. Here, we present an investigation of the surface structure of SrLaAlO4 (001) substrates using surface x-ray diffraction under UHV conditions (10−10 Torr) with the substrate held at either room temperature or 650 °C. Best-fit models using a 1:1 ratio of Sr:La showed significant distortions to the surface AlO6 octahedra.
An anti-noise algorithm based on locally linear embedding and weighted XGBoost for fault diagnosis of T/R module
Authors: He Wei , Yin Baiqiang , Yuan Zhijie , Wu Wei , Min Zhixian
Published: November 2023

Due to the noise accompanied with fault signals, it is challenging to identify the discriminant information and the local geometric feature from the complex fault data for enhancing fault diagnosis accuracy. To address this challenge, this work proposed an anti-noise algorithm based on locally linear embedding integrated with diffusion distance and maximum correntropy criterion (DMLLE). In DMLLE, diffusion distance was adopted instead of the Euclidean distance for neighborhood construction. Meanwhile, the optimal weights were updated to reveal local geometry information based on the loss function of the maximum correntropy criterion. Subsequently, DMLLE is eventually developed to further restrain noise embedding into raw signals and obtain low dimensional features. Furthermore, weighted extreme gradient boosting is used to map the low dimensional features to the types of faults, which easily implements fault pattern recognition. Finally, two synthetic manifold datasets and fault data acquired from the transmit/receive (T/R) module are used to validate the performance of the proposed diagnosis methodology. Compared with the existing methods, the proposed diagnosis methodology generates a smoother flow structure by preserving the local neighborhood of the dataset with noises and realizes a higher accuracy of 94.41% on the T/R module dataset, which outperforms 3%–9% better than other classification models. Therefore, it can be concluded that the proposed diagnosis methodology can effectively extract intrinsic fault features by weakening the influence aroused by noise and achieve superior accuracy in fault diagnosis by addressing the problem of small sample size.
Bulk-like ferroelectricity and magnetoelectric response of low-temperature solution-processed BiFeO3–PbTiO3 films on Ni for metallic MEMS
Authors: Algueró Miguel , Zia Layiq , Jiménez Ricardo , Amorín Harvey , Bretos Iñigo , Barreto Adriana , Jaffari G. Hassnain , Rodríguez-Castellón Enrique , Ramos Pablo , Calzada M. Lourdes
Published: November 2023

Simple and cost-effective procedures for the direct integration of ferroelectric perovskite oxides into Ni structures are necessary to realize related multifunctional metallic microelectromechanical systems, such as dual-source energy harvesters. This is especially difficult in the case of lead-containing morphotropic phase boundary materials for high piezoelectric response because the two components are thermodynamically incompatible and the formation of NiOx or perovskite oxide reduction takes place depending on the processing conditions. We show here that low-temperature solution processing is an effective means to kinetically limit nickel oxidation, capable of providing BiFeO3–PbTiO3 films on Ni plates at only 500 °C. Bulk-like ferroelectric properties and a distinctive magnetoelectric response were attained. This perovskite system, not explored before on Ni, has a much larger switchable polarization than the widely studied Pb(Zr,Ti)O3, and it is shown here to present an excellent downscaling behavior of ferroelectric properties until the verge of the nanoscale.
Exploration of changes in the chemical composition of sedimentary organic matter and the underlying processes during biodegradation through advanced analytical techniques
Authors: Derrien Morgane , Jeanneau Laurent , Jardé Emilie , Hur Jin , Kim Sunghwan
Published: November 2023

Environmental context Organic matter (OM) biodegradation plays a key role as it is one of the main processes causing changes in the amount, composition and properties of OM in sediment. However, a complete understanding of its processes and mechanisms is still not reached. In this study, we aim to explore the chemical composition changes during biodegradation and identify underlying processes. Rationale Although the scientific community has widely investigated organic matter biodegradation processes, only a limited number of studies have explored the molecular changes of this material, whereas its structure, composition and origin play a key role in these processes. Methodology We decided to examine the effects of biodegradation on the chemical composition of sedimentary organic matter and to explore the underlying mechanisms. We conceived a laboratory-based degradation experiment utilising organic-rich sediments artificially composed of two contrasting organic matter end-members (i.e. soil and algae) under two oxygen conditions. The sediment samples before and after incubation were then analysed by laser desorption ionisation–Fourier-transform–ion cyclotron resonance–mass spectrometry for molecular characterisation and by thermally assisted hydrolysis and methylation gas chromatography–mass spectrometry in order to offer insights into the mechanisms driving the biodegradation processes. Results Our results from molecular characterisation unveiled distinct pathways of biodegradation contingent upon the source material. Moreover, they hinted at a predilection for altering high molecular weight compounds like lignin & carboxylic-rich alicyclic molecules (CRAM) and condensed aromatic structures (CAS), manifesting as a conversion into lower molecular weight counterparts. Furthermore, the complementary findings from biomarker analyses underscored the influence of environmental factors – specifically oxygen conditions and microbial communities – on organic matter decomposition. Discussion Although this study is a controlled laboratory experiment and more studies are needed, it demonstrates the intricate interplay among chemical, biological and environmental factors that profoundly shape the reactivity of organic matter. This study underscores the critical need for persistent inquiry, aimed at unravelling the factors and conditions governing the diverse pathways of biodegradation.
Listening to the “noise” in the data
Authors: Munro Murray J.
Published: November 2023

The term “noise” is often applied to the seemingly random variability that always appears in human data, and which
is assumed to be of no interest to the researcher. Some of this variability is unavoidably due to measurement tools or the way in
which we use them, and some is due to the unstable nature of human behaviour. In such cases, we may be justified in treating the
variability as irrelevant noise. However, we cannot assume that all inexplicable variation is unimportant. Using
examples from earlier research, I will argue that individual variability is a phenomenon worthy of study in its own right. Not
only can it help us understand the nuances of the learning process, but giving it careful consideration can be a valuable step in
determining how to effectively apply research findings in pedagogy.
Fluidic motion patterns in English and Modern Greek
Authors: Dalpanagioti Thomai
Published: November 2023

This paper investigates conceptual and phraseological patterns from a cross-linguistic perspective. The focus of attention is on the fluidic motion uses of the highly polysemous verbs run and τρέχω ‘run’ in English and Modern Greek respectively. They are manner of motion verbs denoting the typically human, fast movement on ground and they are frequently cited in the literature on motion event encoding; yet, their extended use to denote motion of liquids is mentioned only in passing. The study thus provides a comprehensive description of that part of the semantic network of the two verbs that relates to fluidic motion (literally and figuratively). The contrastive approach taken combines cognitive semantics (Frame Semantics, Conceptual Metaphor and Metonymy Theory) with a phraseological view of language. Convergences and divergences are identified at a conceptual and phraseological level through a twofold corpus-based study involving comparable monolingual analysis and parallel corpus investigation.
Towards an optimised deep brain stimulation using a large-scale computational network and realistic volume conductor model
Authors: Spiliotis Konstantinos , Butenko Konstantin , Starke Jens , van Rienen Ursula , Köhling Rüdiger
Published: November 2023

Objective. Constructing a theoretical framework to improve deep brain stimulation (DBS) based on the neuronal spatiotemporal patterns of the stimulation-affected areas constitutes a primary target. Approach. We develop a large-scale biophysical network, paired with a realistic volume conductor model, to estimate theoretically efficacious stimulation protocols. Based on previously published anatomically defined structural connectivity, a biophysical basal ganglia-thalamo-cortical neuronal network is constructed using Hodgkin–Huxley dynamics. We define a new biomarker describing the thalamic spatiotemporal activity as a ratio of spiking vs. burst firing. The per cent activation of the different pathways is adapted in the simulation to minimise the differences of the biomarker with respect to its value under healthy conditions. Main results. This neuronal network reproduces spatiotemporal patterns that emerge in Parkinson’s disease. Simulations of the fibre per cent activation for the defined biomarker propose desensitisation of pallido-thalamic synaptic efficacy, induced by high-frequency signals, as one possible crucial mechanism for DBS action. Based on this activation, we define both an optimal electrode position and stimulation protocol using pathway activation modelling. Significance. A key advantage of this research is that it combines different approaches, i.e. the spatiotemporal pattern with the electric field and axonal response modelling, to compute the optimal DBS protocol. By correlating the inherent network dynamics with the activation of white matter fibres, we obtain new insights into the DBS therapeutic action.
Removal of some Heavy Metals from Industrial Wastewater and Gray Water by using some Natural and Organic Materials
Authors: Hameed Dhiaa Zahim , Naser Kadhim Makki
Published: November 2023

A study was conducted for knowing the quantity and quality of heavy metal ions adsorbed on surfaces of treatment materials used in treatment of polluted water and to know the most efficient in removal process. Study included conducting two experiments, the first is laboratory, which is treatment of two polluted waters, namely industrial water and gray water, using four natural treatment materials as filters, which are activated Charcoal, Eichhornia crassipes plant powder, Ceratophyllum plant powder, and Arundo donax plant powder. It used poles made of polyethylene with a length of 100 cm and a diameter of 10 cm equipped with a tap from bottom, a layer of glass wool was placed at bottom, and then treatment materials were placed on top of it at a height of 50 cm. A piece of gauze cloth was placed over it for filtering polluted water from solids. Polluted water was passed after being filtered from top of column and left for 24 hours for equilibrium, then filtrate was collected from bottom of column. Second experiment, it is liberation experiment for heavy metals adsorbed on treated materials, where heavy metals were extracted by a 0.005M concentration of DTPA solution. This process was repeated five times for same treatment material and concentration of heavy metals adsorbed was measured each time. Results showed the following: 1-High concentrations of heavy metals, each of Lead, Cadmium, Zinc and Nickel in industrial water, where they reached 5.190, 0.043, 3.727 and 0.371 mg L-1, respectively, exceeding the limits allowed by World Food and Health Organization for each of Cadmium, Zinc and Nickel, while concentrations of Lead is within internationally permitted limits. As for the gray water, concentrations of Cadmium excelled the internationally permitted limits, while concentrations of Lead, Zinc and Nickel were within internationally permitted limits. 2-Concentration of Lead and Cadmium in all materials used in bioremediation, with exception of coal, exceeded internationally permitted limits in plants. Concentrations of Zinc and Nickel in all materials used in bioremediation did not exceed the internationally permitted limits, while coal did not record the presence of Zinc and Nickel because it is a porous, burned carbonaceous material. 3-Increasing amount of heavy metals liberated from various treatment materials through bioreclamation process in first three extractions, then it began to gradually decrease in fourth and fifth extractions. The different treatment materials varied in amount of heavy metals released, and they can be arranged as follows in terms of amount released of heavy metals: Eichhornia crassipes plant powder > Ceratophyllum plant powder > activated charcoal > Arundo donax plant powder. 4-Highest amount of heavy metals was released from materials used in industrial water, then gray water for Lead and Cadmium, while treatment materials used in industrial water and then gray water excelled in amount released for elements Zinc and Nickel.
Response Water Productivity and Sorghum Yield to Deficit Irrigation Under Surface Drip Irrigation System
Authors: Ibrahim Wallada Muammer , Ati Alaa Salih , Majeed Shatha Salim
Published: November 2023

A field experiment was conducted during the spring season of 2022 in a clay loam soil at the experimental station of the College of Agricultural Engineering Sciences, University of Baghdad - Al-Jadriya, in order to study the effect of deficit irrigation on the growth and productivity of Sorghum, using the surface drip irrigation system, the experiment included irrigation treatments with six levels of full irrigation treatment FI100 When 50% of the available water is depleted, it is compensated by the American evaporation basin class A, from which the deficit irrigation treatments 80, 70, 60, 50, and 40% of the complete irrigation were applied, using the RCBD with three replications. The treatments were applied during the included plant growth stages (vegetative growth, flowering and maturity). Crop growth indicators were measured at the end of the season. Sorghum seeds were sown on 3-13-2022 and harvested on 7-15-2022. The results showed that the seasonal water consumption of corn reached its highest value when the full irrigation treatment was 487.24 mm when 50% of the available water was depleted, then it decreased to 413.59, 376.94, 340.29, 303.63, and 266.98 mm for the deficit irrigation treatments (80, 70, 60, 50, and 40%) calculated from the control treatment (FI%100). Irrigation treatment (FI 100%) gave the highest values for average plant height, leaf area, chlorophyll content, total root dry weight and yield. Water consumption amounted to 413.59 and 376.94 mm compared to the full irrigation treatment, while the treatments (60, 50 and 40) % of the full irrigation were superior in that they saved an amount of water at the expense of low crop productivity. The highest water productivity was recorded at two irrigation treatments minus 80 and 70% for the Sorghum bicolorcrop. It amounted to 13.71 and 15.13 kg m3, as the lack of 20 and 30% of the irrigation water did not affect the productivity. It is recommended to irrigate at a rate of 80 and 70% of the total ETa, which indicates the possibility of providing 20 and 30% of the full irrigation needs without affecting the grain yield.
Effects of Nano-Fipronil on Male Rats’ Biochemical, Liver, and Renal Functions
Authors: Al-Janabi Qassim Ammar Ahmood , Hamed Lamees Noori , Ibraheem Aqeel Khaleel
Published: November 2023

Fipronil has been widely employed for crop protection over the past decade because of its low soil stability and insecticidal potency at modest application rates. The present study was designed to investigate the adverse effects of sub-acute exposure to 10 and 20 mg/kg/b. w. of Nano-Fipronil on biochemical blood profile and histological parameters in male rats according to the permissible limits of acceptable daily intake (ADI). The results hematological parameters indicated that Red blood cells (RBCs) and Hemoglobin(H.b) decreased in all treated groups compared with the control. While PLT and white blood cells (WBCs) was significantly increased in all treated groups compared with the control. The toxicity of effects of nano-fipronil pesticides leads to higher levels of liver function parameters (AST, ALT and ALP), kidney function (Blood urea and Creatinin and Uric acid) and Oxidative stress (MDA, GSH and CAT) results demonstrated highly significant differences (P≤0.05) in all groups treated compared with the control.
Evaluation of Genetic Performance and Estimation of some Genetic Parameters in Yield Traits and Components of Four Genetic Structures of Broad Bean Under the Influence of Different Levels of Soil Salinity
Authors: Merhij Mohammed Y. , Al-Khafaji Hamzah Mohsin Kadhim
Published: November 2023

The study was carried out with the aim of evaluating the genetic performance and estimating some genetic parameters in the characteristics of the yield and its components for the four different structures originating from Broad bean (local, Turkish, Spanish and Dutch) under the influence of different levels of soil salinity (2, 6 and 9 ds\m) in the field of the Field Crops Department of the Faculty of Agriculture - Al-Qasim Green University During the growing season of 2022/2023, the experiment was carried out according to the design of the complete random sectors as a factor experiment and with three replicates. The results of the analysis of variance showed significant differences between the four structures of all the traits studied. The Turkish variety significantly outperformed the rest of the other varieties in all the characteristics studied Number of pods (10.12 pods / plant), the number of seeds per pod (4.06 seeds / pod) and the weight of 100 seeds (121.22 g) and the yield of seeds (1.59 tons / ha) and the biological yield (3.19 tons / ha) and protein yield 322.4 kg / ha). pod) weighing 100 seeds (135.02 g), seed yield (2.42 tons/ha), biological yield (4.42 tons/ha) and protein yield 0.507 ton/ha), The results showed that the phenotypic and genetic variations were high for all traits at the level (2 ds/m) but decreased at the salt level (9 ds/m). The percentage of inheritance in the broad sense was very high for all traits and all salt levels, which indicates that the phenotypic variation between the varieties was mostly genetic.
Morpho-Molecular Identification and First Report of Trichoderma Aggressivum is Causing Green Rot on White Button Mushroom in Iraq
Authors: Taha Abdulrasool Shallal , Jamel Dareen S. , Abdui-Razzak Ahmad K.
Published: November 2023

The aim of this study was to morphological isolation and identification of fungus associated with the fruits and culture media of the white mushroom Agaricus bisporus. The results of isolation and identification from the sampling areas included Baghdad, Babylon, and Diwaniyah. Besides, Sulaymaniyah governorates showed the association of seven species of fungi associated the fruiting body and culture media of the white mushroom A. bisporus represented by the two pathogens Cladobotryum spp. and Trichoderma spp. As well as, the competitive fungi of A. bisporus culture medium, such as Aspergillus spp. and Penicillium spp. and Phoma sp. and Rhizopus spp., and Ulocladium sp. The most common pathogenic fungus was Cladobotryum spp. with a frequency of 56.2%, followed by Trichoderma spp., with a frequency of 54.1%, which appeared in samples from two sampling areas. Conversely, species T. aggressivum recorded a frequency of 42.5%, which is the first record in Iraq on the fruits and media of white fungus. The fungus Aspergillus spp. showed the existence percentage reached 65.5%, which is the highest among the competing fungi, followed by Penicillium spp., with an existence percentage of 26.6%. Then, Rhizopus spp., Phoma sp., and Ulocladium sp. with a frequency of 16.6%, 10.4%, and 10.4%, respectively. The results of the pathogenicity of the fungus isolate Trichoderma spp. indicated that all the isolates tested for the pathogenicity of the fruiting bodies of the white mushroom A. bisporus led to the infection of the fruiting bodies and their transformation into brown color and damage. The isolates of the fungus T. aggressivum (isolate 1 and isolate 2) recorded a disease severity of 60.0% and 60.0%, respectively. While, at a temperature of 4 °C, the isolates of the fungus T. aggressivum (1 and 2) recorded a disease severity amounted to 40.0% and 50.0%, respectively, compared to the control treatment without fungus, where the disease severity amounted to 0.0%. The results of the molecular identification of the DNA of the T. aggressivum, which showed the highest pathogenicity of A. bisporus fruiting bodies, using the specialized primer ITSI/ITS4, as it gave bands with a molecular weight of 600 bp. These findings were compared with the GenBank with a high similarity for the fungus T. aggressivum and it has been deposited in the Gen Bank with the accession number (OQ109172).
The flowability and high-temperature resistance of manufactured sand concrete: An exploration for high-rise buildings
Authors: Ren Zhiping , Hua Jianmin , Wang Huichao , Hou Chunming , Du Fuxiang , Huang Lepeng , Huo Xiaowei
Published: November 2023

The depletion of natural concrete aggregates, e.g., river sands, is a gradual process, and hence, manufactured sand concrete (MSC) is widely used in various construction projects. The flowability and high-temperature resistance of MSC directly determine the transport of fresh concrete and the fire resistance of high-rise buildings. In this study, MSC with different superplasticizer contents and sand ratios was prepared and its flowability and high-temperature resistance were studied. Scanning electron microscopy (SEM) and mercury intrusion porosimetry (MIP) were used to characterize the microstructure and porosity of MSC. The flowability of MSC with higher than 0.75% superplasticizer content or lower than 43% sand ratio is suitable for super high-rise buildings according to GB/T 50081-2019. The mechanical properties of other MSC meet the C30 requirements except for the MSC with a sand ratio of 48%. And the relatively high superplasticizer content or low sand ratio can make the denser structure and lower porosity of MSC. In addition, the MSC with relatively high superplasticizer content and low sand ratio exhibits better resistance to high temperatures due to a denser structure. This study provides theoretical guidance for using MSC in high-rise buildings and studying fire performance.
Tungsten nanostructure growth by sputtering and redeposition in BCA-MD-KMC hybrid simulation
Authors: Ito Atsushi M , Takayama Arimichi , Nakamura Hiroaki
Published: November 2023

The formation mechanism of fibrous tungsten nanostructures, fuzz, induced by helium plasma irradiation on tungsten materials has been investigated. We have developed a BCA-MD-KMC hybrid simulation, which solves the injection process of helium atoms by the Binary Collision Approximation (BCA) method, the diffusion process of helium atoms in tungsten materials by the Kinetic Monte-Carlo (KMC) method, and the deformation of tungsten materials due to helium bubbles by the Molecular Dynamics (MD) method. In addition, the model used to calculate the recoiling of tungsten atoms in BCA was improved to account for the reduced binding energy of tungsten atoms on rough surfaces. Using the hybrid simulation, the height of the nanostructures reached about 50 nm. The main mechanism of nanostructure growth was that sputtering and redeposition caused transport of tungsten atoms perpendicular to the surface. The present simulation was able to represent not only the dependence that the nanostructure height increases in proportion to the square root of the helium fluence, but also the existence of incubation fluence before the growth starts.
Examining the influence of Scandium interlayer and parameters on the mechanical behaviour in FSW of AA 5754-H111 plate through response surface approach
Authors: Suresh Raj L , Manimaran G
Published: November 2023

Friction stir welding (FSW) was conducted on 5754-H111 aluminium alloy using a response surface methodology to examine the impact of process parameters on the efficiency of the weld. The key FSW parameters were the percentage of scandium inclusion in the interlayer, tool rotational speed, and tool travel speed. The significant responses were identified as the tensile strength of the weld and the hardness in the weld zone. An Al-Mg-Sc alloy was employed as an interlayer material between the 5754 plates to enhance the strength in the weld zone. The addition of Scandium had a more pronounced effect on the hardness of the stir zone. The tensile strength was increased by raising the tool’s rotational speed. The results showed that the maximum tensile strength of the joints was 225 MPa and the hardness was highest at 118 HV1 in the weld stir zone. The introduction of Scandium improved the joint strength by producing fine grains and Al3Sc precipitates. The welding speed had the least impact on the tensile properties of the joint among all the variables investigated.
Improved polarimetric analysis of human skin through stitching: advantages, limitations, and applications in dermatology
Authors: Jütte Lennart , Patel Harshkumar , Roth Bernhard
Published: November 2023

Polarimetry is a powerful tool for the analysis of the optical properties of materials and systems, such as human skin. However, in many polarimetric setups, the field of view is limited to a few square centimeters. In these cases, it is possible to resort to stitching techniques, which involve combining multiple Mueller matrix measurements obtained from different overlapping regions of the sample. In this paper, we propose a stitching technique for polarimetric data and discuss its advantages and limitations. We also describe the potential of image stitching for improving the accuracy and robustness of in vivo polarimetry in the presence of random patient movement. We conducted our research using a diverse set of samples which included porcine skin, human skin from arms and fingers, cold cuts of chicken and gelatine, alongside synthetically created sample data. Our results demonstrate the effectiveness of this technique for the application in dermatology. Each additional in vivo measurement enhances the field of view by approximately one third, thereby considerably augmenting the total observation area. We show that stitching enables for the polarimetric assessment of large skin patches which is useful for the diagnosis of inflammatory skin diseases.
Highly sensitive strain sensors based on dispensing technology for human–machine interaction
Authors: Chen Zhifu , Huang Liangsong , Zhang Peng , Li Yuxia , Bu Xiaofei , Chen Huake , Tan Jiapeng
Published: November 2023

Flexible strain sensors have stable and sensitive sensing performance under deformation conditions such as pressing, bending, and stretching. However, the preparation process of high-performance strain sensors is still very complex, which also limits the application and production of sensors. At the same time, most sensors are unstable and inefficient, so they cannot meet people’s expectations for high sensitivity and stability. In order to solve the above problems, this paper proposes a resistive strain sensor based on dispensing technology, with carbon black and polyurethane mixture as printing ink. Then, a sensor-sensitive layer with a right-angle serpentine structure is printed directly by air pressure extrusion. The sensor can detect changes at 0.1% strain and withstand 2400 tensile cycles while maintaining a sensitivity of 28.07 in the range of 0%–40%. In addition, the sensor can accurately and stably reflect the changes in different joints of the human body. At the same time, the data glove based on the strain sensor shows great application potential in the fields of gesture recognition and human–machine interaction.
Study on the matching rules and control mechanisms between flocculants and slurry settlement characteristics
Authors: Wang Wuchao , Fan Lei , Ni SongBo , Wei Jihong , Huang Yiping
Published: November 2023

In order to realise efficient, economic, low carbon and environmentally friendly slurry disposal, floc sedimentation velocity (S

f
), supernatant volume (V

s
), water content of bottom mud (W

b
), supernatant turbidity (N

s
) and pH value were determined by slurry sedimentation tests, specific resistance tests, and water quality analysis. Orthogonal tests were performed to analyze the matching rule and control mechanism between flocculants and the slurry settlement characteristics. The results show that polyaluminum chloride (PAC) and polyferric chloride (PFC) had a low dose and a fast sedimentation rate. The sedimentation effect of 20 ionic degree cationic polyacrylamide (CPAM-20) in organic flocculant is the best. Although flocculants can shorten the sedimentation time, excessive flocculants can also weaken the slurry separation effect. The sedimentation efficiency of organic flocculants is higher than that of inorganic flocculants, but it is easy to form foam on the supernatant surface. For the composite flocculants, the sensitivity sequence of S

f
, V

s
and W

b
is PAC>CPAM-20>PFC. PAC plays a controlling role in the sedimentation effect of the slurry.
Net zero emission buildings: a review of academic literature and national roadmaps
Authors: Þórólfsdóttir Elín , Árnadóttir Áróra , Heinonen Jukka
Published: November 2023

Addressing the growing issue of climate change demands active measures. With its significant carbon footprint, the building industry needs to make immediate efforts contributing to achieving the Paris Agreement’s objective of restricting global warming to 1.5 °C. This review focuses on net zero emission buildings (NZEBs) which are claimed to offer a viable option to significantly reduce greenhouse gas emissions from the built environment. The review covers both the recent academic literature on NZEBs, and the NZEB roadmaps from the member organizations of the World Green Building Council, focusing on those Green Building Councils actively working to implement NZEBs in their local contexts. By synthesizing a broad range of viewpoints and practices derived from academic literature and roadmaps, this review provides a holistic overview of the different perspectives to the current state of NZEBs and to their future. The review shows that NZEBs have the potential to provide significant environmental, economic, and social advantages, improving the built environment’s overall sustainability. The review also promotes a more thorough understanding over NZEBs that can facilitate collaborative policymaking and action amongst stakeholders.
Exploring non-linear modes of the subtropical Indian Ocean Dipole using autoencoder neural networks
Authors: Ibebuchi Chibuike Chiedozie
Published: November 2023

The subtropical Indian Ocean Dipole (SIOD) significantly influences climate variability, predominantly within parts of the Southern Hemisphere. This study applies an autoencoder—a type of artificial neural network (ANN)—known for its ability to capture intricate non-linear relationships in data through the process of encoding and decoding—to analyze the spatiotemporal characteristics of the SIOD. The encoded SIOD pattern(s) is compared to the conventional definition of the SIOD, calculated as the sea surface temperature (SST) anomaly difference between the western and eastern subtropical Indian Ocean. The analysis reveals two encoded patterns consistent with the conventional SIOD structure, predominantly represented by the SST dipole pattern south of Madagascar and off Australia’s west coast. During different analysis periods, distinct variability in the global SST patterns associated with the SIOD was observed. This variability underscores the SIOD’s dynamic nature and the challenges of accurately defining modes of variability with limited records. One of the ANN patterns has a substantial congruence match of 0.92 with the conventional SIOD pattern, while the other represents an alternate non-linear pattern within the SIOD. This implies the potential existence of additional non-linear SIOD patterns in the subtropical Indian Ocean, complementing the traditional model. When global temperature and precipitation are regressed onto the ANN temporal patterns and the conventional SIOD index, both appear to be associated with anomalous climate conditions over parts of Australia, with several other consistent global impacts. Nevertheless, due to the non-linear nature of the ANN patterns, their effects on local temperature and precipitation vary across different regions as compared to the conventional SIOD index. This study highlights that while the conventional SIOD pattern is consistent with the ANN-derived SIOD pattern, the climate system’s complexity and non-linearity might require ANN modeling to advance our comprehension of climatic modes.
Visual Perception in the Human Brain: How the Brain Perceives and Understands Real-World Scenes
Authors: Bartnik Clemens G. , Groen Iris I. A.
Published: November 2023

How humans perceive and understand real-world scenes is a long-standing question in neuroscience, cognitive psychology, and artificial intelligence. Initially, it was thought that scenes are constructed and represented by their component objects. An alternative view proposed that scene perception starts by extracting global features (e.g., spatial layout) first and individual objects in later stages. A third framework focuses on how the brain not only represents objects and layout but how this information combines to allow determining possibilities for (inter)action that the environment offers us. The discovery of scene-selective regions in the human visual system sparked interest in how scenes are represented in the brain. Experiments using functional magnetic resonance imaging show that multiple types of information are encoded in the scene-selective regions, while electroencephalography and magnetoencephalography measurements demonstrate links between the rapid extraction of different scene features and scene perception behavior. Computational models such as deep neural networks offer further insight by how training networks on different scene recognition tasks results in the computation of diagnostic features that can then be tested for their ability to predict activity in human brains when perceiving a scene. Collectively, these findings suggest that the brain flexibly and rapidly extracts a variety of information from scenes using a distributed network of brain regions.
KinScan: AI-based rapid profiling of activity across the kinome
Authors: Brahma Rahul , Shin Jae-Min , Cho Kwang-Hwi
Published: November 2023

Kinases play a vital role in regulating essential cellular processes, including cell cycle progression, growth, apoptosis, and metabolism, by catalyzing the transfer of phosphate groups from adenosing triphosphate to substrates. Their dysregulation has been closely associated with numerous diseases, including cancer development, making them attractive targets for drug discovery. However, accurately predicting the binding affinity between chemical compounds and kinase targets remains challenging due to the highly conserved structural similarities across the kinome. To address this limitation, we present KinScan, a novel computational approach that leverages large-scale bioactivity data and integrates the Multi-Scale Context Aware Transformer framework to construct a virtual profiling model encompassing 391 protein kinases. The developed model demonstrates exceptional prediction capability, distinguishing between kinases by utilizing structurally aligned kinase binding site features derived from multiple sequence alignment for fast and accurate predictions. Through extensive validation and benchmarking, KinScan demonstrated its robust predictive power and generalizability for large-scale kinome-wide profiling and selectivity, uncovering associations with specific diseases and providing valuable insights into kinase activity profiles of compounds. Furthermore, we deployed a web platform for end-to-end profiling and selectivity analysis, accessible at https://kinscan.drugonix.com/softwares/kinscan.
Ensemble-GNN: federated ensemble learning with graph neural networks for disease module discovery and classification
Authors: Pfeifer Bastian , Chereda Hryhorii , Martin Roman , Saranti Anna , Clemens Sandra , Hauschild Anne-Christin , Beißbarth Tim , Holzinger Andreas , Heider Dominik
Published: November 2023

Federated learning enables collaboration in medicine, where data is scattered across multiple centers without the need to aggregate the data in a central cloud. While, in general, machine learning models can be applied to a wide range of data types, graph neural networks (GNNs) are particularly developed for graphs, which are very common in the biomedical domain. For instance, a patient can be represented by a protein–protein interaction (PPI) network where the nodes contain the patient-specific omics features. Here, we present our Ensemble-GNN software package, which can be used to deploy federated, ensemble-based GNNs in Python. Ensemble-GNN allows to quickly build predictive models utilizing PPI networks consisting of various node features such as gene expression and/or DNA methylation. We exemplary show the results from a public dataset of 981 patients and 8469 genes from the Cancer Genome Atlas (TCGA).

Availability and implementation

The source code is available at https://github.com/pievos101/Ensemble-GNN, and the data at Zenodo (DOI: 10.5281/zenodo.8305122).
regioneReloaded: evaluating the association of multiple genomic region sets
Authors: Malinverni Roberto , Corujo David , Gel Bernat , Buschbeck Marcus
Published: November 2023

Motivation

Next-generation sequencing methods continue improving the annotation of genomes in part by determining the distribution of features such as epigenetic marks. Evaluating and interpreting the association between genomic regions and their features has become a common and challenging analysis in genomic and epigenomic studies.

Results

With regioneR we provided an R package allowing to assess the statistical significance of pairwise associations between genomic region sets using permutation tests. We now present the R package regioneReloaded that builds upon regioneR’s statistical foundation and extends the functionality for the simultaneous analysis and visualization of the associations between multiple genomic region sets. Thus, we provide a novel discovery tool for the identification of significant associations that warrant to be tested for functional interdependence.

Availability and implementation

regioneReloaded is an R package released under an Artistic-2.0 License. The source code and documentation are freely available through Bioconductor: http://www.bioconductor.org/packages/regioneReloaded.
Towards an accurate autism spectrum disorder diagnosis: multiple connectome views from fMRI data
Authors: Yang Jie , Xu Xiaowen , Sun Mingxiang , Ruan Yudi , Sun Chenhao , Li Weikai , Gao Xin
Published: November 2023

Functional connectome has revealed remarkable potential in the diagnosis of neurological disorders, e.g. autism spectrum disorder. However, existing studies have primarily focused on a single connectivity pattern, such as full correlation, partial correlation, or causality. Such an approach fails in discovering the potential complementary topology information of FCNs at different connection patterns, resulting in lower diagnostic performance. Consequently, toward an accurate autism spectrum disorder diagnosis, a straightforward ambition is to combine the multiple connectivity patterns for the diagnosis of neurological disorders. To this end, we conduct functional magnetic resonance imaging data to construct multiple brain networks with different connectivity patterns and employ kernel combination techniques to fuse information from different brain connectivity patterns for autism diagnosis. To verify the effectiveness of our approach, we assess the performance of the proposed method on the Autism Brain Imaging Data Exchange dataset for diagnosing autism spectrum disorder. The experimental findings demonstrate that our method achieves precise autism spectrum disorder diagnosis with exceptional accuracy (91.30%), sensitivity (91.48%), and specificity (91.11%).