bluuebunny/crossref_metadata_2025 huggingface dataset:
The physical soldier caste of an invasive, human-infecting flatworm is morphologically extreme and obligately sterile
Authors: Metz Daniel C. G. , Hechinger Ryan F.
Published: July 2024

We show that the globally invasive, human-infectious flatworm,
Haplorchis pumilio
, possesses the most physically specialized soldier caste yet documented in trematodes. Soldiers occur in colonies infecting the first intermediate host, the freshwater snail
Melanoides tuberculata
, and are readily distinguishable from immature and mature reproductive worms. Soldiers possess a pharynx five times absolutely larger than those of immature and mature reproductives, lack a germinal mass, and have a different developmental trajectory than reproductives, indicating that
H. pumilio
soldiers constitute a reproductively sterile physical caste. Neither immature nor mature reproductives showed aggression in in vitro trials, but soldiers readily attacked heterospecific trematodes that coinfect their host. Ecologically, we calculate that
H. pumilio
caused ~94% of the competitive deaths in the guild of trematodes infecting its host snail in its invasive range in southern California. Despite being a dominant competitor,
H. pumilio
soldiers did not attack conspecifics from other colonies. All prior reports documenting division of labor and a trematode soldier caste have involved soldiers that may be able to metamorphose to the reproductive stage and have been from nonhuman-infectious marine species; this study provides clear evidence for an obligately sterile trematode soldier, while extending the phenomenon of a trematode soldier caste to freshwater and to an invasive species of global public health concern.
Directed evolution of material-producing microorganisms
Authors: Laurent Julie M. , Jain Ankit , Kan Anton , Steinacher Mathias , Enrriquez Casimiro Nadia , Stavrakis Stavros , deMello Andrew J. , Studart André R.
Published: July 2024

Nature is home to a variety of microorganisms that create materials under environmentally friendly conditions. While this offers an attractive approach for sustainable manufacturing, the production of materials by native microorganisms is usually slow and synthetic biology tools to engineer faster microorganisms are only available when prior knowledge of genotype–phenotype links is available. Here, we utilize a high-throughput directed evolution platform to enhance the fitness of whole microorganisms under selection pressure and identify genetic pathways to enhance the material production capabilities of native species. Using
Komagataeibacter sucrofermentans
as a model cellulose-producing microorganism, we show that our droplet-based microfluidic platform enables the directed evolution of these bacteria toward a small number of cellulose overproducers from an initial pool of 40,000 random mutants. Sequencing of the evolved strains reveals an unexpected link between the cellulose-forming ability of the bacteria and a gene encoding a protease complex responsible for protein turnover in the cell. The ability to enhance the fitness of microorganisms toward a specific phenotype and to unravel genotype–phenotype links makes this high-throughput directed evolution platform a promising tool for the development of new strains for the sustainable manufacturing of materials.
Stochastic machine learning via sigma profiles to build a digital chemical space
Authors: Abranches Dinis O. , Maginn Edward J. , Colón Yamil J.
Published: July 2024

This work establishes a different paradigm on digital molecular spaces and their efficient navigation by exploiting sigma profiles. To do so, the remarkable capability of Gaussian processes (GPs), a type of stochastic machine learning model, to correlate and predict physicochemical properties from sigma profiles is demonstrated, outperforming state-of-the-art neural networks previously published. The amount of chemical information encoded in sigma profiles eases the learning burden of machine learning models, permitting the training of GPs on small datasets which, due to their negligible computational cost and ease of implementation, are ideal models to be combined with optimization tools such as gradient search or Bayesian optimization (BO). Gradient search is used to efficiently navigate the sigma profile digital space, quickly converging to local extrema of target physicochemical properties. While this requires the availability of pretrained GP models on existing datasets, such limitations are eliminated with the implementation of BO, which can find global extrema with a limited number of iterations. A remarkable example of this is that of BO toward boiling temperature optimization. Holding no knowledge of chemistry except for the sigma profile and boiling temperature of carbon monoxide (the worst possible initial guess), BO finds the global maximum of the available boiling temperature dataset (over 1,000 molecules encompassing more than 40 families of organic and inorganic compounds) in just 15 iterations (i.e., 15 property measurements), cementing sigma profiles as a powerful digital chemical space for molecular optimization and discovery, particularly when little to no experimental data is initially available.
Exploring positional and dimensional aspects of topographic space for advanced-level British Sign Language
learners
Authors: Nunn Nicola
Published: July 2024

This study investigates how British Sign Language (BSL) learners develop positional and dimensional aspects of
topographic space. The teaching of BSL has been occurring at an increasing rate, and many people are learning to use BSL to the
advanced levels, which are generally referred to in the UK as BSL Levels 4 and 6 and are loosely equivalent to pre-C1 (advanced)
and C1 (proficient), respectively, on the Common European Framework for Reference (Languages) scale. Spatial grammar is a crucial
aspect of BSL (Brennan 1992), and this article provides insight into issues related to
learning how to use topographic space, a feature of spatial grammar whereby real-world referent locations are replicated in the
signing production. This study of L2 advanced learners of BSL explores the numbers and types of errors that are made when applying
topographic features into their signing, with a particular focus on positioning and dimensionality aspects. Two scenarios are used
do this: classroom layouts (Task 1) and a courtroom layout (Task 2). The study concludes with reflections on how BSL teachers can
support L2 learners in improving their development of topographic skills.
ω-Grammotoxin-SIA inhibits voltage-gated Na+ channel currents
Authors: Collaço Rita de Cássia , Van Petegem Filip , Bosmans Frank
Published: July 2024

ω-Grammotoxin-SIA (GrTX-SIA) was originally isolated from the venom of the Chilean rose tarantula and demonstrated to function as a gating modifier of voltage-gated Ca2+ (CaV) channels. Later experiments revealed that GrTX-SIA could also inhibit voltage-gated K+ (KV) channel currents via a similar mechanism of action that involved binding to a conserved S3–S4 region in the voltage-sensing domains (VSDs). Since voltage-gated Na+ (NaV) channels contain homologous structural motifs, we hypothesized that GrTX-SIA could inhibit members of this ion channel family as well. Here, we show that GrTX-SIA can indeed impede the gating process of multiple NaV channel subtypes with NaV1.6 being the most susceptible target. Moreover, molecular docking of GrTX-SIA onto NaV1.6, supported by a p.E1607K mutation, revealed the voltage sensor in domain IV (VSDIV) as being a primary site of action. The biphasic manner in which current inhibition appeared to occur suggested a second, possibly lower-sensitivity binding locus, which was identified as VSDII by using KV2.1/NaV1.6 chimeric voltage-sensor constructs. Subsequently, the NaV1.6p.E782K/p.E838K (VSDII), NaV1.6p.E1607K (VSDIV), and particularly the combined VSDII/VSDIV mutant lost virtually all susceptibility to GrTX-SIA. Together with existing literature, our data suggest that GrTX-SIA recognizes modules in NaV channel VSDs that are conserved among ion channel families, thereby allowing it to act as a comprehensive ion channel gating modifier peptide.
A relativistic scalar model for fractional interaction between dark matter and gravity
Authors: Benetti Francesco , Lapi Andrea , Gandolfi Giovanni , Liberati Stefano
Published: July 2024

In a series of recent papers we put forward a ‘fractional gravity’ framework striking an intermediate course between a modified gravity theory and an exotic dark matter (DM) scenario, which envisages the DM component in virialized halos to feel a non-local interaction mediated by gravity. The remarkable success of this model in reproducing several aspects of DM phenomenology motivates us to look for a general relativistic extension. Specifically, we propose a theory, dubbed Relativistic Scalar Fractional Gravity or RSFG, in which the trace of the DM stress-energy tensor couples to the scalar curvature via a non-local operator constructed with a fractional power of the d’Alembertian. We derive the field equations starting from an action principle, and then we investigate their weak field limit, demonstrating that in the Newtonian approximation the fractional gravity setup of our previous works is recovered. We compute the first-order post-Newtonian parameter γ and its relation with weak lensing, showing that although in RSFG the former deviates from its GR values of unity, the latter is unaffected. We also perform a standard scalar-vector-tensor-decomposition of RSFG in the weak field limit, to highlight that gravitational waves propagate at the speed of light, though also an additional scalar mode becomes dynamical. Finally, we derive the modified conservation laws of the DM stress energy tensor in RSFG, showing that a new non-local force emerges, and hence that the DM fluid deviates from the geodesic solutions of the field equations.
Marker points 3D matching based on Delaunay triangfulation structure and error dispersion
Authors: Jin Ruidi , Wang Zhao , Huang Junhui , Li Zijun , Duan Qiongqiong , Qi Miaowei , Wang Wei , Dong Qiang
Published: July 2024

Point cloud registration techniques based on marker points are widely used in optical 3D industrial measurements. However, in this process, marker points 3D matching methods are often haunted by low efficiency and accuracy. To improve the performance of marker points 3D matching, we propose a two-step method of ‘matching-verification’. In the matching process, Delaunay triangulation is introduced to extract the 3D structure of the marker points set, and then the 3D structure is deconstructed into 2D units for matching, which simplifies complexity and improves the efficiency of the algorithm. In the verification process, the mismatched pairs of points are located and removed by the method that is based on the error dispersion of initial matched results, and the initial transformation results are iteratively verified to obtain the optimal transformation matrix. The experimental results show that our method takes an average of 2.2 s for each matching, the average error of coarse registration point cloud is 0.075 mm and the root mean square is 0.219 mm, which effectively solves the problem of the low efficiency and accuracy of marker points 3D matching methods.
PPP based on factor graph optimization
Authors: Xiao Guorui , Xiao Zhengyang , Zhou Peiyuan , Jia Xiaoxue , Wang Ningbo , Zhao Dongqing , Wei Haopeng
Published: July 2024

Kalman or Kalman-related filtering methods are routinely applied in precise point positioning (PPP). However, in robot simultaneous localization and mapping (SLAM) systems, factor graph optimization (FGO) has proven advantages over filtering methods in recent years, e.g. reducing the linearization error and support of plug-and-play features for multiple sensor fusion. Therefore, it would be interesting to apply the FGO to PPP. In addition, it will also facilitate the tight integration of PPP with Visual/LiDAR SLAM. In this work, PPP is solved under the FGO framework. A factor graph for PPP has been constructed. Results from 268 IGS-MGEX stations show that the FGO method can achieve a similar performance to that of Kalman filtering. First, the positioning accuracy in the convergence period can be improved for PPP based on FGO because it optimizes the entire state variables based on all the available observations. For applications that do not require real-time processing, the observation after the current state, e.g. future observations, can also be used to enhance the current state estimation. Second, the accuracy of static PPP is almost the same for the two methods with millimeter-accuracy for horizontal directions and centimeter-accuracy for vertical directions. Third, the kinematic PPP for both methods can achieve centimeter-level accuracy in horizontal directions and decimeter-level accuracy in vertical directions. Although the performance is comparable, it is noted that the computational efficiency of the FGO method is still a problem. For each epoch, the average elapsed time for Kalman filtering is 132 microseconds, while that of FGO method is 9664 microseconds. The elapsed time of the FGO method can be further improved if the fix-window optimization technique is applied, which will be investigated in the future.
A fault diagnosis approach for flange stabilizer based on multi-signal fusion
Authors: Chen Fan , Wei Haotian , Li Yong , Wang Luming , Xu Lushuai , Dong Shaohua , Zhang Hang
Published: July 2024

As an essential means of energy transportation, pipelines have been widely used in various fields. However, many external factors such as vibration and corrosion can cause damage at the flange part, which seriously affects the safety of pipeline transportation. Quite a number of methods for troubleshooting at pipeline flanges have been continuously proposed, yet there is little research on diagnostic methods for the stabilizer at the flange. Therefore, in this paper, we focus on the stabilizer of the flange and a method that combines traditional detection and machine learning with each other to detect stabilizer faults is proposed. At first, we can obtain a stable and reliable diagnostic data by combining the advantages of the preload of the bolt and the acoustic signal. Subsequently, the optimized N-Beats model is trained based on the measured bolt preload data to predict the service state of the stabilizer. Finally, the data measured by the sensors as well as the predicted data are analyzed by a simplified classification algorithm to determine whether a fault has occurred and to classify the fault. The fault detection method used in this paper not only improves the accuracy of detection and shortens the fault detection time, but also improves the automation level of pipeline inspection. Hence, the work done in this paper has far-reaching practical significance for ensuring the safe and stable operation of pipelines.
Deep quality-related stacked isomorphic autoencoder for batch process quality prediction
Authors: Zhang Yan , Cao Jie , Zhao Xiaoqiang , Hui Yongyong
Published: July 2024

Batch processes play an important role in modern chemical industrial and manufacturing production, while the control of product quality relies largely on online quality prediction. However, the complex nonlinearity of batch process and the dispersion of quality-related features may affect the quality prediction performance. In this paper, a deep quality-related stacked isomorphic autoencoder for batch process quality prediction is proposed. Firstly, the raw input data are reconstructed layer-by-layer by isomorphic autoencoder and the raw data features are obtained. Secondly, the quality-related information is enhanced by analyzing the correlation between the isomorphic feature of each layer of the network and the output target, and constructing a correlation loss function. Thirdly, a deep quality-related prediction model is constructed to predict the batch process quality variables. Finally, experimental validation was carried out in penicillin fermentation simulation platform and strip hot rolling process, and the experimental results demonstrated the feasibility and effectiveness of the model proposed in this paper for the quality prediction of the batch process.
Transformer fault diagnosis based on DBO-BiLSTM algorithm and LIF technology
Authors: Yan Pengcheng , Wang Jingbao , Wang Wenchang , Li Guodong , Zhao Yuting , Wen Ziming
Published: July 2024

In response to the deficiencies of traditional power transformer fault detection techniques, such as low sensitivity and the inability for online monitoring, a novel transformer fault diagnosis model combining laser-induced fluorescence (LIF) technology with deep learning is proposed. Initially, the spectral data of transformer insulation oil is acquired using LIF technology, yielding spectral data for various fault types. Subsequently, MinMaxScaler and standard normalized variate methods are employed for denoising and preprocessing the spectral data. The preprocessed data is then subjected to dimensionality reduction using linear discriminant analysis and T-distributed stochastic neighbor embedding to ensure that the spectral data retains maximal feature information while minimizing its dimensionality. Following this, long short-term memory, bidirectional long short-term memory (BiLSTM), dung beetle optimizer-BiLSTM, convolutional neural network, and support vector machine models are constructed. The reduced-dimensional data is fed into each of the five models for training to facilitate transformer fault diagnosis. Through comparative analysis among the five models, the optimal model is selected. Experimental results indicate that the dung beetle optimization-BiLSTM model is the most suitable for transformer fault diagnosis in this experiment, underscoring its significant implications for ensuring the safety of power systems.
Wm-algebras and fractional powers of difference operators
Authors: Beffa Gloria Marí
Published: July 2024

In this paper we define a Poisson pencil associated to a latticeWm-algebras defined in a recent paper by Izosimov and Marí Beffa (2023Int. Math. Res. Not.202317021–59). We then prove that this Poisson pencil is equal to the one defined in 2013 by Marí Beffa and Wang (2013Nonlinearity262515) and the author using a type of discrete Drinfel’d–Sokolov reduction. We then show that, much as in the continuous case, a family of Hamiltonians defined by fractional powers of difference operators commute with respect to both structures, defining the kernel of one of them and creating an integrable hierarchy in the Liouville sense.
From minimum-viable-products to full models: a step-wise development of diagnostic forward models in support of design, analysis and modelling on the ST40 tokamak
Authors: Sertoli Marco , Alieva A , Buxton P F , Dnestrovskii A , Gemmell M , Lowe H , O’Gorman T , Osin D , Sladkomedova A , Varje J , Willett H V , Wood J , Lomanowski Bart A , Delabie E , Marchuk O , Litherland-Smith E , Collie K , Gadgil S ,   the Tokamak Energy Team
Published: July 2024

Like most magnetic confined fusion experiments, the ST40 tokamak started off with a small subset of diagnostics and gradually increased the diagnostic set to include more complex and comprehensive systems. To make the most of each operational phase, forward models of various diagnostics are used and developed to aid design, provide consistency-checks during commissioning, test analysis methods, and build workflows to constrain high-level parameters to inform interpretation, theory and modelling. For new models and new analysis workflows, minimum-viable-products are released early, and their complexity is increased in a step-wise manner, facilitating the support of all programme phases on multiple parallel applications, while enabling learning opportunities and feedback loops. In this contribution we review the philosophy, scope and architecture of the framework under development. We discuss the details of some forward models, with examples on how they are used to aid diagnostic design, to investigate analysis methodologies through synthetic data, and how they are embedded in experimental analysis workflows. We compare previously published experimental results with new, more advanced analysis workflows employing more recent, detailed models and new diagnostic data, providing confirmation of the published material from the 2021–22 experimental campaign.
Variations of plasma potential in RF discharges with DC-grounded electrode
Authors: Hiret Paul , Tognina Patrik , Faudot Eric , Steiner Roland , Dmitriev Artem , Marot Laurent , Meyer Ernst
Published: July 2024

The self-bias voltage

V

bias

and the plasma potential

V

p

are the key parameters to control plasma-wall interactions in radio-frequency (RF) asymmetric plasma discharges. Knowing these two parameters allows to monitor the ion energy distribution on the electrode surface. However, in a direct current (DC) coupled plasma, the plasma potential increased to hundreds of volts while no more

V

bias

developed on the driven electrode. In addition, the plasma potential is strongly impacted by the electrode-wall area ratio. Several analytical or semi-analytical models exist to explain this phenomenon and to approximate the plasma potential, knowing the electrode-wall area ratio considering capacitive sheaths or a combination of resistive and capacitive sheaths. The

V

p

and several other plasma parameters were investigated experimentally with a Langmuir probe and a Retarding field energy analyser for different electrode/wall area ratios in low-temperature RF plasma. The validity of the models was studied for an extensive range of area ratios with different pressures and RF driving amplitude. Moreover, the presence of strong stochastic heating of the plasma for area ratios below 6 was evidenced by an increased ion flux and an increased electron temperature.
SPR based dual parameter wide range curling pot shaped photonic crystal fiber sensor
Authors: Guo Pengxiao , Du Huijing , Li Jianshe , Li Yuxin , Li Shuguang , Yin Zhiyong , Wang Ruiduo , Li Kaifeng , Li Hongwei , Li Xingwei
Published: July 2024

This article proposes a curling pot shaped photonic crystal fiber (PCF) sensor based on surface plasmon resonance (SPR), which utilizes two parallel polished surfaces in the cladding to achieve dual parameter measurements of liquid refractive index (RI) and temperature. The mode characteristics and sensing performance of the designed PCF sensor are studied using the finite element method, and the effects of changes in structural parameters such as pore radius, spacing, and gold film thickness on the resonance spectrum are analyzed. The sensing accuracy of the sensor is insensitive to the change of structural parameters, and it has the characteristics of a wide detection range, high sensitivity, and easy manufacture. When the measured RI is in the range of 1.33∼1.42, the maximum RI sensitivity is 20400 nm RIU−1, and the maximum FOM is 483.3 RIU−1. When the temperature ranges from −10 °C to 100 °C, the maximum sensitivity is 15.4 nm °C−1, and the maximum FOM is 0.43 RIU−1. The tight structure design of the sensor core close to the polishing surface and the anti-spill light design with a uniform arrangement of air holes enhance the SPR effect, which is the essential reason for achieving a wide detection range and high sensitivity.
Investigations for the heat treatment effects on permeability of some semi-permeable membranes
Authors: Abdel-Hai S I , El-Tonsy M M , El-Henawey M I
Published: July 2024

The current study aims to devise a mechanism that can regulate the permeability of semi-permeable membranes, either by enhancing or reducing it, based on their intended application. This approach seeks to offer a straightforward and efficient method for controlling membrane permeability. Cellulose acetate (CA) and cellulose triacetate (CTA) membranes were subjected to two different heat treatment processes. One method involved thermal annealing at relatively high temperatures, while the other method involved freezing the membranes when they were saturated with water. A special osmosis cell was designed and utilized to quantify the flow rates across the treated CA and CTA membranes. Our findings indicate that subjecting the membranes to high-temperature annealing decreased the flow rate. Conversely, the freezing treatment boosted the flow rate, thereby enhancing membrane permeability. This approach could pave the way for numerous applications across various fields.
Effects of nanocutting environments on the electronic structure of armchair-type graphene nanoribbons: the first-principles study
Authors: Tang Meiling , Yuan Zewei , Sun Jingting , He Yan , Ran Di , Wang Ying , Feng Yusen , Zhou Xinbo
Published: July 2024

In order to investigate the effect of nanocutting environment on the electronic structure of armchair-type graphene nanoribbons, this paper adopts a first-principle computational approach to study the effect of different substrates and solutions, such as on the motion of electrons in the middle and outer orbitals of graphene nanoribbons, by observing the energy band structure, the value of the band gap, and the density of the split-wave states. The results show that the adsorption of Si and C atoms at the edge of the nanoribbon leads to a decrease in the band gap value. The adsorption of Al and O atoms at the edges of graphene nanoribbons leads to a decrease in the nanoribbon band gap value to 0 eV. Different substrate atoms mainly affect the p-orbital electron motion in the nanobelt. Bare-edge graphene nanoribbons are indirect bandgap structures, and graphene nanoribbons with H, O and OH atoms adsorbed at the edges of the nanoribbons are direct bandgap structures. Edge O-isation leads to a nanobelt band gap of 0, which exhibits metallic properties. The edge H-isation nanoribbon band gap is higher than the bare edge nanoribbon band gap. Nanoribbon edge OH-isation reduces the nanoribbon band gap value. Nanoribbon edge adsorption of atoms in solution affects p-orbital electron motion. The formation energy of five-ring defects and seven-ring defects is low, and the defects are easier to form. The edges containing defects all reduce the band gap values of graphene nanoribbons. The defects mainly affect the p-orbital electron motion, leading to differences in the band gap values. The bandgap decreases with increasing nanobelt width, and the bandgap value conforms to 3 N+2<3 N<3 N+1, with regular fluctuations in the curve with period 3. The larger the band gap, the smaller the curvature of the curve at the extremes, and the sparser the curve. In this paper, the electronic structures of different edge structures are analysed from a quantum mechanical point of view, and the synthesis of these results will provide theoretical guidance for obtaining high-quality semiconductor nanoribbons by mechanochemical nanocutting.
Cosmological constraints on the background dynamics of a two-field nonsingular bounce model
Authors: Ri Kang Song , Hwang Sin Chol , Ri Hyon Chol
Published: July 2024

In this study, we consider a nonsingular two-field bounce scenario with non-minimal kinetic coupling between two scalar fields. We derive constraints on the model parameters from the finiteness of the physical quantities at the classical level and from the relation between the late-time accelerated expansion and particle production up to the bounce phase. We then determine the allowed parameter space for the model.
Divertor heat load estimates on NSTX and DIII-D using new and open-source 2D inversion analysis code
Authors: Adebayo-Ige P.O. , Gan K.F. , Lasnier C.J. , Maingi R. , Wirth B.D.
Published: July 2024

A thermography inversion algorithm has been developed in the open-source Python-based computer code, HYPERION, to calculate the heat flux incident on plasma-facing components (PFCs) in axisymmetric tokamaks. The chosen mesh size at the surface significantly affects the calculated transient heat flux results. The calculated transient heat flux will exceed the real value when the mesh size tends to zero but will underestimate the real value when the mesh size is large. A criterion for determining the appropriate mesh size for the transient heat flux calculation will be discussed. The numerical scheme for HYPERION uses a 2D fully implicit finite-difference approach, allowing temperature-dependent thermal properties of PFC materials. The inversion algorithm is benchmarked against established heat flux calculation codes, TACO and THEODOR, based on thermography data from NSTX and DIII-D respectively. The primary benefits of HYPERION compared to TACO and THEODOR are that it is open-source and it allows for the optimization of mesh thickness along the substrate. The algorithm also accounts for the thermal properties of thin surface layers that characteristically form on PFCs due to plasma-material interactions. The agreement between HYPERION and THEODOR is excellent, as the percent difference between the codes is ∼5% on average in the case of the DIII-D data for moderate to high heat flux. Verification tests with TACO show slightly higher average percent differences of 8% and 12%. In using HYPERION to study filaments in heat flux, the initial results indicate that small ELMs filaments significantly broaden the divertor heat flux, and decrease divertor peak flux. Compared to the inter-ELM, the small ELM filaments decrease the divertor peak surface temperature. With intermittent divertor filaments, the divertor heat flux width is comparable with that found in L-mode.
Blended lime plasters with biomass ash and natural fibres reinforcement
Authors: Keppert M , Pommer V , Šádková K , Botnari A , Vejmelková E , Koňáková D
Published: July 2024

The possibility to valorise biomass combustion ash in air lime based plaster was evaluated by means of mechanical properties. The possible effect of vegetable fibres (hemp, flax) was examined as well. The biomass ash improved significantly the mechanical properties of plaster. On the other hand, the vegetable fibres are limiting the compressive strength due to lower wettability between fibres and lime. However the fibres had positive effect on bending strength, as it is expected. The surface modification of fibres seems to be necessary in order to improve their performance in the lime system.
Mechanical properties of blended cements affected by impurities in thermally activated clays
Authors: Šádková K. , Pommer V. , Vejmelková E. , Koňáková D.
Published: July 2024

With the scarcity of raw materials, energy intensiveness and environmental burden connected with producing Portland cement, there is a growing need to find substitute binders. Thermally activated clay also appears to be a suitable material for partial cement replacement. However, not all clays are the same. It depends very much on the place of collection, its chemical and phase composition, and the activation temperature. This study compared six different types of clays fired at 600 °C in terms of quantitative phase analysis and mechanical strength results. In addition to the fineness of grinding and firing temperature, the clay composition had an immense impact on mechanical properties. Content of illite up to 20% was found to be beneficial, as this clay reached the highest mechanical strengths. Regarding the quartz, its presence did not harm the overall performance of thermally activated clays and the presence of calcite could cause the improvement of the mechanical strengths. However, the clay with the most miscellaneous composition caused the deterioration of compressive strength but reached much higher bending strength compared to pure cement.
Sol gel synthesis of TiO2@ZnO composites for self-cleaning and antimicrobial coating
Authors: Bruzl D. , Bocian L. , Sokola P. , Másilko J. , Sedlačík M. , Švec J. , Bartoníčková E. , Šoukal F.
Published: July 2024

In recent years, the development of advanced materials for applications in self-cleaning surfaces and antimicrobial coatings has received considerable attention due to its potential impact on environmental sustainability and public health. Among the emerging materials, metal oxide-based photocatalysts have shown promise in addressing these challenges. In this context, the present study focuses on the promise sol-gel synthesis and potential photocatalytic properties of TiO2@ZnO (x = 0.6 - 0.9) nano-scaled particles, with particular emphasis on their applications in self-cleaning and microbial coatings. The choice of TiO2@ZnO (x = 0.6 - 0.9) as the subject of investigation is driven by the advantageous properties of both titanium dioxide (TiO2) and zinc oxide (ZnO). TiO2 is known for its exceptional photocatalytic activity, while ZnO is known for its antimicrobial properties. By combining these two metal oxides in a controlled manner, we aim to harness their synergistic effects to create a multifunctional material with enhanced performance. A titanium (IV) isopropoxide and zinc acetate dihydrate have been used as precursors for the so-gel process. The synthesised powders were evaluated by X-ray diffraction analysis and Raman spectroscopy to determine the allotropy of TiO2 and possible lattice distortions. The optical band gap (Egap) was evaluated by molecular reflection UV-VIS spectroscopy. In addition, size and morphology were determined by scanning electron microscopy (SEM).
Utilization of alternative wood particles for modern thermal insulation products
Authors: Zach J , Peterková J , Novák V , Korjenic A
Published: July 2024

Thermal insulation materials play a vital role in minimising energy loss in building operation and also affect the amount of greenhouse gas emissions associated with heating and cooling. In this context, it is becoming an increasingly important milestone to find suitable thermal insulation materials that not only meet the technical requirements but also minimise their environmental impact. The trend towards the use of eco-friendly materials for thermal insulation reflects the construction industry’s desire to contribute to environmental protection and the transition to more sustainable models of building construction and renovation. For more than 20 years, a number of research teams have been investigating the possibility of replacing synthetically produced materials such as mineral wool and polystyrene foam with natural fibre-based insulation materials. These alternatives include wood as a traditional, easily renewable raw material. This, together with the low energy intensity of processing and manufacturing wood materials, contributes to its low carbon footprint. Compared to traditional synthetic insulation materials, which are often energy intensive to produce, wood is a more environmentally friendly choice. However, with many European countries now facing a potential shortage of higher quality wood, it is necessary to look for alternative sources of wood, including in the field of thermal insulation materials, materials with a lower carbon footprint that can be produced from lower quality wood or from wood waste that would otherwise only have an energy use. The paper is devoted to the study and use of suitable wood waste and secondary raw materials from spruce wood (coarse wood chips, sawdust and wood flour) for the development of modern thermal insulations with the aim of an environmentally friendly and less energy-intensive production process compared to conventional insulants.
Characterization and damage of the historic brick masonry of the Zákupy castle stables
Authors: Frankeová D , Bauerová P , Náhunková P , Slížková Z , Polák A M
Published: July 2024

A chemical-mineralogical analysis and mechanical tests of historical bricks were carried out as part of the construction-technical survey. The objective was to identify the causes of significant masonry decay. The ruined agricultural yard is a national cultural monument. Conservators believe that the historical importance exceeds that of the neighbouring castle. Stables were designed in 1650 by prominent Italian builders Giulio Broggio and Giovanni Domenico Orsi. The building has not been maintained since the conclusion of World War I. After removal from the masonry, the analyzed samples of bricks reached a very high, almost total degree of water saturation - 87-94%. Some bricks are heavily contaminated with nitrates and sulfates, infrared spectrometry analysis showed that calcium nitrate tetrahydrate is the most abundant of the nitrates. The determined average values of physical properties (bulk weight 1764 kg/m3, capillary absorption 13.6% by weight and open porosity 24% by volume) from samples under atmospheric pressure are comparable to the values of masonry bricks produced today. The results of the tests on the bricks from the Zákupy Castle stables construction demonstrate the high manufacturing quality of the masonry elements utilized. Based on the results of the analyses, it can be assumed that three degradation factors contribute to the observed damage to the bricks: high wetting of the masonry (almost total saturation of pores with water), which is most likely long-term lasting, frost cycles - repeated freezing and thawing of water in the bricks during the winter months, and repeated crystallization of water-soluble salts present in pores near the surface.
Constraining future surface air temperature change on the Tibetan Plateau
Authors: Wang Jianyu , Zhai Panmao , Zhou Baiquan , Li Chao , Chen Yang
Published: July 2024

The rapid warming of the Tibetan Plateau (TP) in recent decades has led to severe consequences, including the melting of glaciers and snow cover, which further accelerates warming. Accurately projecting the magnitude of future warming is crucial for effective climate change adaptation. However, the projection of future temperature change is model dependent. In this study, we demonstrate a significant correlation between the historical inter-model warming trend and future temperature change, suggesting this relationship could be used to calibrate the best estimate of projections and reduce the uncertainty by observations. For a high emission scenario, the constraint helps to narrow down the uncertainty range of annual and summer temperature change on the western TP by up to 2 °C and 4 °C, respectively, in the end of this century. The most substantial calibrated increase of future change is in winter by up to 2 °C, followed by autumn with an increase by about 1 °C. Discrepancies of historical warming trend among different observation datasets expose the largest impact on the constrained best estimate compared with emergent relationship derived from different climate models and warming trend in different historical periods.
Low-cost porous transport layers for water electrolysis cells with polymer electrolyte membranes
Authors: Wakayama Hiroaki
Published: July 2024

Proton exchange membrane (PEM) water electrolysis has advantages over other methods of producing green hydrogen such as its excellent response to power input fluctuations; wide operating range of current density; ease of production of high-pressure, high-purity hydrogen; and high durability. However, the conventional precious metal coatings used on the bipolar plates (BPPs) and porous transport layers (PTLs) of the PEM water electrolysis cell to prevent their oxidation are problematic because of their high cost; indeed, the BPPs and PTLs combined are the largest contributor (50%–70%) to the total cost of PEM water electrolysis stacks. Here, the Pt-coated PTL on the oxygen electrode side of a PEM water electrolysis cell was replaced with one with an alternative low-cost material coating (Ti4O7 or NiTiP), and the water electrolysis characteristics of the system were evaluated. We found that Ti4O7, but not NiTiP, functioned as a conductive, corrosion-resistant PTL coating in the PEM water electrolysis cell.
Assessment of bioaccumulation factors of trace metals for Upper Gangetic fish
Authors: Saxena Vyom
Published: July 2024

The River Ganga basin is home to over 520 million people and 2500 species of flora and fauna, including several fish species. This study determines the bioaccumulation factors of fish for five trace metals, namely Cu, Fe, Zn, Mn, and Cr, in a stretch of the River Ganga in the upper Gangetic alluvial plain with limited industrial activities. The abundance of different trace metals in the water follows the order Fe > Zn > Mn > Cu > Cr. The concentrations in fish show a slightly different pattern and follow the relative quantitative order as Zn >≈ Fe >Mn > Cu >Cr. The trace metal levels in fish are well below the permissible limits set by various regulatory agencies. The bioaccumulation factor values are in order Zn>Cr>Mn>Cu>Fe. This stretch of the Ganga has not been extensively investigated for bioaccumulation by aquatic organisms. These values, therefore, represent site-specific baseline data for future anthropogenic activities that may affect the trace metal profile in this part of the Gangetic aquatic system. The study is also significant due to the presence of the Narora nuclear power plants, as the bioaccumulation factors of stable elements help predict the behavior of their radioactive counterparts and homologous elements in the environment.
Investigation of diodic behavior in p-NiO/n-SnO2 bilayer heterojunctions fabricated via DC magnetron reactive sputtering
Authors: Adline Shermin , Bhat Prashant , Kekuda Dhananjaya
Published: July 2024

Tin oxide (SnOx) thin films at varying oxygen flow rates and Nickel oxide (NiO) thin films were deposited by reactive dc magnetron sputtering on glass substrates. Structural, chemical, morphological, optical and electrical properties of the deposited films were studied. XRD studies confirmed that the deposited films were polycrystalline in nature. SnOx thin films have shown two phases such as SnO and SnO2. AFM and SEM were used to analyse the morphology of the films and EDS confirmed the presence of Sn and Ni in the respective films. The examination of the x-ray photoelectron spectrum showed that the sputtered SnOx films contain both Sn2+ and Sn4+ oxidation states and NiO films contain Ni+2 and Ni+3 oxidation states. Photoluminescence study shows strong violet and weak red emission peaks for SnOx films and NiO showed strong emission peaks in the orange-red region. The optical results demonstrate that the films were transparent. The bandgap of SnOx and NiO samples were ∼3.3 eV and − 3.42 eV, respectively. Further we constructed a p-NiO/n-SnO2 heterojunction diode and its electrical characteristics were thoroughly assessed. Using dark current–voltage measurements, electrical characteristics such saturation current, ideality factor and barrier height were determined. The increase in oxygen flow rate led to reduction in the rectification of the devices. Our findings support the creation of high-performance metal oxide heterojunction for optoelectronic devices.
Microfluidics-derived microfibers in flexible bioelectronics
Authors: Yang Chaoyu , Hou Xingyu , Zhang Li
Published: July 2024

Flexible electronics have attracted extensive attention across a wide range of fields due to their potential for preventive medicine and early disease detection. Microfiber-based textiles, encountered in everyday life, have emerged as promising platforms with integrated sensing capabilities. Microfluidic technology has been recognized as a promising avenue for the development of flexible conductive microfibers and has made significant achievements. In this review, we provide a comprehensive overview of the state-of-the-art advancements in microfiber-based flexible electronics fabricated using microfluidic platforms. Firstly, the fundamental strategies of the microfluidic fabrication of conductive microfibers with different structures and morphologies are introduced. Subsequently, attention is then directed towards the diverse applications of these microfibers in bioelectronics. Finally, we offer a forward-looking perspective on the future challenges about microfluidic-derived microfibers in flexible bioelectronics.
Introduction
Authors: Drevon Jerome
Published: July 2024

The introductory chapter lays the groundwork for the analysis of how two prominent Jihadi groups, Ahrar al-Sham and Jabhat al-Nusra, emerged as the most formidable players within the Syrian armed opposition before politicising. This chapter presents the theoretical framework of the book, positing that the key difference between Jihadis is how they institutionalise internally and externally, more than any ideological commitment. Additionally, the introductory chapter delves into the distinct characteristics of Jihadis, emphasizing the Jihadi paradox: the features that empower them also prevent them from achieving strategic victories. The book contends that the politicisation of Ahrar al-Sham and then Jabhat al-Nusra was their strategic response to this paradox.
Expanding the Rebellion
Authors: Drevon Jerome
Published: July 2024

Chapter 3 examines the expansion of the armed opposition throughout Syria, focusing on the challenges that armed opposition groups faced when attempting to institutionalise internally and externally to survive after the opposition seized large parts of Syrian territory. While most groups existed in only one of Syria’s distinctive armed opposition-held areas, without developing a presence throughout the country, Ahrar al-Sham and Jabhat al-Nusra were among the few groups that managed to spread in more than one region. Ahrar al-Sham’s development was unique in that it formed in a bottom-up alliance system of many factions that institutionalised their ties to each other before institutionalising internally as a single organisational entity. This unique pattern of development also explains the group’s local embeddedness in Syrian communities, particularly in the northwest.
Uniting the Armed Opposition
Authors: Drevon Jerome
Published: July 2024

Chapter 4 delves into the various efforts to unite and institutionalise the armed opposition (internally as well as externally, with other states) against the backdrop of increased international intervention in the conflict. The need to unify the armed opposition became critical to protect the areas under its control and bolster its credibility. However, most unification attempts were driven primarily by military necessity, leading to further polarisation around the two main contenders for leadership: Jabhat al-Nusra and Ahrar al-Sham. The chapter argues that the outcome of their conflict was largely determined by their diverging internal institutionalisation processes. Jabhat al-Nusra’s emphasis on centralisation and discipline allowed it to maintain a stronger grip on power, ultimately leading to its consolidation as the dominant group in the last remaining Syrian province under opposition control, despite Ahrar al-Sham’s significant strength.
Politicising Jihad
Authors: Drevon Jerome
Published: July 2024

The final chapter explores how the institutionalisation of the armed opposition informed its politicisation. It traces Jihadi ideological revisionism from pre-2011 prisoner debates to the impact of the configuration of the conflict—including the domestic nature of the uprising and factional competition—to explain how new ideas emerged and consolidated in the armed opposition, especially in Ahrar al-Sham. The chapter then focuses on Ahrar al-Sham’s institutional trajectory, examining the group’s struggle to fully embrace the Syrian armed opposition’s revolutionary agenda. Despite being one of the most successful armed groups in Syria, Ahrar al-Sham faced numerous institutional impediments that hindered its ability to fully realise its political aspirations. The final part of the chapter analyses the challenges posed by the rise of Jabhat al-Nusra (as it transformed into HTS), as well as the external subjugation of the armed opposition by Russia and Turkey.