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Flax (Linum usitatissimum) is a bast fiber plant known for its long fibers, making it an excellent source of pulp for paper production. In Ethiopia, flax is primarily cultivated for oil, with the residual straw utilized for papermaking. This study focuses on pulping flax straw using the Kraft process and investigates its chemical composition, proximate analysis, and morphological properties. The proximate analysis revealed an ash content of 4.13% and moisture content of 11%. Chemical composition analysis showed cellulose at 51.34%, hemicellulose at 25.20%, lignin at 14.12%, ash at 4.13%, and extractives at 5.21%. The morphological properties included a fiber length of 1.41 mm, diameter of 16.78 μm, lumen width of 9.45 μm, and cell wall thickness of 3.77 μm. Flax straw exhibited an acceptable Runkel ratio (0.8) and flexibility coefficient (56.32), placing it within the range of non-wood fibers. SEM analysis of the pulp's morphology was conducted to assess fiber structure, including the presence of cracks. Pulp quality and length are directly linked to paper strength. Various pulping conditions were studied using a full-factorial design, with optimum conditions being 10% alkaline, 131.74°C, and 120 min of cooking time, yielding a pulp with a Kappa number of 10.45 and a yield of 40.56%. The resulting paper demonstrated standard tensile, tearing, and burst strengths, indicating that flax straw is a promising raw material for paper production. [ABSTRACT FROM AUTHOR]

In many animals, early-life decisions influence long-term fitness. Mantidflies are spider egg predators; their tiny larvae climb aboard spiders to find eggs, but little is known about how they find spiders. We tested the hypothesis that mantidfly larvae (Dicromantispa sayi) detect and respond to substrate-borne spider cues (e.g., silk and/or excreta). We presented larvae with filter paper exposed to different types of spiders (adult female, adult male, or juvenile Habronattus trimaculatus jumping spiders) versus a no-cue control. Larvae spent more time on filter paper with spider cues. We then tested the hypothesis that mantidflies make finer distinctions between spiders when given direct choices between these cues. Larvae did not discriminate between sexes but spent more time (and exhibited more phoretic behavior) on filter paper with female or male cues compared with juvenile cues. While this suggests that mantidflies actively seek out adult spiders, we also found that adult spiders were more active than juveniles and may have simply deposited more silk and excreta, providing a stronger cue to detect. We discuss these findings in the context of the risks and benefits of different spider hosts, and how early-life spider-searching strategies may shape a mantidfly's long-term fitness. [ABSTRACT FROM AUTHOR]

In many animals, early-life decisions influence long-term fitness. Mantidflies are spider egg predators; their tiny larvae climb aboard spiders to find eggs, but little is known about how they find spiders. We tested the hypothesis that mantidfly larvae (Dicromantispa sayi) detect and respond to substrate-borne spider cues (e.g., silk and/or excreta). We presented larvae with filter paper exposed to different types of spiders (adult female, adult male, or juvenile Habronattus trimaculatus jumping spiders) versus a no-cue control. Larvae spent more time on filter paper with spider cues. We then tested the hypothesis that mantidflies make finer distinctions between spiders when given direct choices between these cues. Larvae did not discriminate between sexes but spent more time (and exhibited more phoretic behavior) on filter paper with female or male cues compared with juvenile cues. While this suggests that mantidflies actively seek out adult spiders, we also found that adult spiders were more active than juveniles and may have simply deposited more silk and excreta, providing a stronger cue to detect. We discuss these findings in the context of the risks and benefits of different spider hosts, and how early-life spider-searching strategies may shape a mantidfly's long-term fitness. [ABSTRACT FROM AUTHOR]

Firecrackers are a vital element of cultural festivities that happen worldwide. However, the hazardous by-products they emit have a significant impact on environmental pollution, leading to the greenhouse effect and climate change. Aluminium powder serves as the fuel in the traditional flash powder mixture, nitrate of potassium serves as an oxidizing agent, and sulphur acts as the igniter at exact concentrations. The presence of sulfur in the flash powder mixture is critical as it acts as an igniter, contributing to the formation of sulfur dioxide, which can cause environmental harm. We carried out an experiment employing Sargassum wightii brown seaweed powder as a replacement for sulphur at specific amounts to lessen the effects of sulphur in flash powder. We discovered that Sargassum wightii brown seaweed powder may replace up to 50% of the sulphur significance in the flash powder mixture without impairing the flash powder's traditional performance. Our experiments included impact and friction sensitivity, SEM, and FTIR analyses to evaluate the improved flash powder composition. The results revealed that the modified flash powder mixture SP5 and SP10 emits less emission by 12% and 21%, and produces similar noise performance of 108 and 107 dB(A) to the normal flash powder composition (SP), affirming that the SP10 flash powder is a viable alternative. Moreover, in our relentless pursuit to mitigate the detrimental effects on our environment, we have ingeniously introduced a novel product—the Chinese cracker made from vegetable waste paper. Not only does this innovative solution address concerns regarding land pollution, but it also presents a sustainable approach to consumer goods. [ABSTRACT FROM AUTHOR]

The pulp and paper industry generates vast quantities of paper sludge, posing significant environmental challenges due to its disposal in landfills or incineration. This study explores the potential of valorizing paper sludge by incorporating it into particleboard production. It aims to optimize sludge content and particle size to enhance board properties—a novel approach to waste management in the wood composites industry. Through systematic variation of sludge content (0–25%) and particle size (< 0.5 to > 2 mm), we assessed the mechanical and physical properties such as internal bond strength (IB), modulus of rupture (MOR), modulus of elasticity (MOE), water absorption (WA), and thickness swelling (TS). The findings indicate that incorporating paper sludge at moderate levels (5–15%) with optimized particle sizes (< 1 mm) significantly improves the mechanical properties of the particleboard, including increased IB, MOR, and MOE while reducing WA and TS. Principal Component Analysis (PCA) further supported these results, revealing that higher-density boards with enhanced mechanical properties absorb less water, highlighting the interrelationship between structural integrity and moisture resistance. The PCA also identified thickness swelling as an independent factor, suggesting that while mechanical properties can be optimized, additional strategies are needed to control swelling. In conclusion, this study demonstrates that up to 15% paper sludge can be effectively used in particleboard production without compromising quality, provided particle size is carefully controlled. This approach not only offers a sustainable solution for managing paper sludge but also contributes to the development of eco-friendly composite materials, aligning with circular economy principles. [ABSTRACT FROM AUTHOR]

Nucleic acid amplification testing has great potential for point-of-need diagnostic testing with high detection sensitivity and specificity. Current sample preparation is limited by a tedious workflow requiring multiple steps, reagents and instrumentation, hampering nucleic acid testing at point of need. In this study, we present the use of mixed cellulose ester (MCE) paper for DNA binding by ionic interaction under molecular crowding conditions and fluid transport by wicking. The poly(ethylene) glycol-based (PEG) reagent simultaneously provides the high pH for alkaline lysis and crowding effects for ionic binding of the DNA under high salt conditions. In this study, we introduce Paper-based Abridged Solid-Phase Extraction with Alkaline Poly(ethylene) Glycol Lysis (PASAP). The anionic mixed cellulose ester (MCE) paper is used as solid phase and allows for fluid transport by wicking, eliminating the need for pipetting skills and the use of a magnet to retain beads. Following the release of DNA from the cells due to the lytic activity of the PASAP solution, the DNA binds to the anionic surface of the MCE paper, concentrating at the bottom while the sample matrix is transported towards the top by wicking. The paper was washed by dipping it in 40% isopropanol for 10 s. After air-drying for 30 s, the bottom section of the paper (3 mm × 4 mm) was snapped off using the cap of a PCR tube and immersed in the colourimetric loop-mediated isothermal amplification (cLAMP) solution for direct amplification and colourimetric detection. The total sample processing was completed in 15 min and ready for amplification. cLAMP enabled the detection of 102 CFU/mL of Escherichia coli (E. coli) from culture media and the detection of E. coli in milk < 103 CFU/mL (10 CFU) after incubation at 68 °C for 60 min, demonstrating applicability of the method to complex biological samples. [ABSTRACT FROM AUTHOR]

This work proposed an approach to multi-component non-metallic materials, namely regular polygonal paper honeycomb sandwich tubes filled with polyethylene (PE) foam, and focused on the influence of drop impact parameters and structural parameters on the deformation characteristics and energy absorption of the filled tubes. Axial drop impact tests were employed to exert drop impact loading on cross-sections of the specimens with a square drop weight. The results showed that the X-direction filled tube (X-DFT) had a higher crushing strength and yield strength than that of the Y-direction filled tube (Y-DFT). As the tubular cross-section edge number of the filled tube increased, the specific energy absorption (SEA) and specific total efficiency (STE) decreased. Under the same axial drop impact loading conditions, the SEA and STE of the X-DFT were superior to those of the Y-DFT. As the edge number of the tubular cross-section or the tubular length ratio increased, the SEA and STE of the filled honeycomb tube decreased significantly. While the impact energy increased, the SEA and STE of the filled tubes increased approximately linearly. This work investigated the influence of drop-impact and structural parameters on deformation characteristics and energy absorption. It is expected to provide supplementary documentation for the advancement of cushion protection technology and the optimization of product structure. [ABSTRACT FROM AUTHOR]

The creativity of scientists often manifests as localized hot streaks of significant success. Understanding the underlying mechanisms of these influential phases can enhance the effectiveness of support systems and funding allocation, fostering groundbreaking discoveries worthy of accolades. Historically, analyses have suggested that hot streaks occur randomly over time. However, our research, through meticulous examination, reveals that these phases are not flatly distributed but are more frequent at the early and late stages of scientists' careers. Notably, both early and late hot streaks are marked by dense tie collaborations, with the former typically involving close partnerships with particular authors and the latter being characterized by involvement in large-scale projects compared with single-top or ordinary papers. This pattern indicates that mid-career researchers lack both intimate relations and resources to keep big projects, leading to "mid-career pitfall" of consecutive success. This insight holds profound implications for the development of policies and initiatives aimed at bolstering innovative research and discovery. [ABSTRACT FROM AUTHOR]

Traditionally, cellulose nanofiber (CNF) production has primarily relied on virgin cellulose sources. Yet, the shift to using paper mill sludge (PMS) as a source for CNF underscores the significance of reusing and recycling industrial byproducts. PMS contains significant amounts of cellulose that can be extracted as a raw material. The purpose of present study is to provide a sustainable approach to PMS utilization as a paper coating additive in the cellulose nanofibrils (CNFPMS) form via simply scalable wire-wound rod coating method. The effect of CNFPMS additive amounts at two coating layers on microstructure and surface properties of coatings such as porosity, air permeability surface roughness and optical properties such as brightness, gloss and CIE L*a*b* is studied, which they can also provide insight for the eventual print performance. Results indicated that the obtained CNFPMS in paper coating shows 52% decrease in porosity, presenting significant improvement in the coating microstructure. The marginal increase in permeability coefficient and surface roughness, 54% and 10%, respectively, suggests improving color reproduction and preventing color density losses. Optical analysis showed slight decrease in brightness and gloss, as was expected. Notably, the lightness was improved, which also indicates increasing color gamut volume in printing applications. As a result, the current work offers a sustainable approach to manage PMS for use in paper coatings as a high-value-added material. [ABSTRACT FROM AUTHOR]

Anger suppression is important in our daily life, as its failure can sometimes lead to the breaking down of relationships in families. Thus, effective strategies to suppress or neutralise anger have been examined. This study shows that physical disposal of a piece of paper containing one's written thoughts on the cause of a provocative event neutralises anger, while holding the paper did not. In this study, participants wrote brief opinions about social problems and received a handwritten, insulting comment consisting of low evaluations about their composition from a confederate. Then, the participants wrote the cause and their thoughts about the provocative event. Half of the participants (disposal group) disposed of the paper in the trash can (Experiment 1) or in the shredder (Experiment 2), while the other half (retention group) kept it in a file on the desk. All the participants showed an increased subjective rating of anger after receiving the insulting feedback. However, the subjective anger for the disposal group decreased as low as the baseline period, while that of the retention group was still higher than that in the baseline period in both experiments. We propose this method as a powerful and simple way to eliminate anger. [ABSTRACT FROM AUTHOR]

Microfluidic paper-based analytical devices often are combined with scanners as detectors. In this work, different scanning options offered by scanners: resolution, scanning mode, exposure to radiation, colour restoration, and saving format were tested. Moreover, different attempts to mathematical data treatment based on intensities of three channels—Red, Green and Blue, were studied. All measurements presented in this article were conducted for a model dye—bromothymol blue and a model analyte—zinc(II) ion (complexed with xylenol orange in a paper matrix). The article summarizes the scanning options and possibilities of mathematical calculations. Nevertheless, it is suggested that the best option is to use the prior prepared calculation file to paste obtained intensities and compare all presented in this article (and the most frequently used) equations to process intensities and decide which one should be used in the particular analysis. [ABSTRACT FROM AUTHOR]

Metagenomics has revolutionized access to genomic information of microorganisms inhabiting the gut of herbivorous animals, circumventing the need for their isolation and cultivation. Exploring these microorganisms for novel hydrolytic enzymes becomes unattainable without utilizing metagenome sequencing. In this study, we harnessed a suite of bioinformatic analyses to discover a novel cellulase-degrading enzyme from the camel rumen metagenome. Among the protein-coding sequences containing cellulase-encoding domains, we identified and subsequently cloned and purified a promising candidate cellulase enzyme, Celcm05-2, to a state of homogeneity. The enzyme belonged to GH5 subfamily 4 and exhibited robust enzymatic activity under acidic pH conditions. It maintained hydrolytic activity under various environmental conditions, including the presence of metal ions, non-ionic surfactant Triton X-100, organic solvents, and varying temperatures. With an optimal temperature of 40 °C, Celcm05-2 showcased remarkable efficiency when deployed on crystalline cellulose (> 3.6 IU/mL), specifically Avicel, thereby positioning it as an attractive candidate for a myriad of biotechnological applications spanning biofuel production, paper and pulp processing, and textile manufacturing. Efficient biodegradation of waste paper pulp residues and the evidence of biopolishing suggested that Celcm05-2 can be used in the bioprocessing of cellulosic craft fabrics in the textile industry. Our findings suggest that the camel rumen microbiome can be mined for novel cellulase enzymes that can find potential applications across diverse biotechnological processes. [ABSTRACT FROM AUTHOR]

Trimethylsilyl cellulose (TMSC) was employed as the coating matrix for the application of zinc oxide nanoparticles (ZnO) onto paper surfaces and the protections of ZnO/TMSC coating against UV-induced damages and fungal spoilage were evaluated. Filter papers were immersed in 2% w/v TMSC solution loaded with ZnO and air-dried. Three ZnO/TMSC suspensions were prepared with 0.1, 0.5, and 1% w/v ZnO NPs. The presences of ZnO/TMSC protective layers were confirmed with ATR-IR spectroscopy. The coated papers exhibited high surface hydrophobicities. After the coated papers were subject to 365-nm UV irradiation at 400 W for 3 h, the contact angles dramatically dropped. The trimethylsilyl (TMS) groups exposed on the surface formed a moisture barrier and were partially removed on UV exposure. ATR-IR revealed that more TMS groups were removed in the protective layer with no ZnO. UV-irradiated papers turned yellow and papers protected with 1% ZnO/TMSC exhibited significantly lower color changes than that of the uncoated one. Compared to the TMSC-coated paper, the addition of ZnO resulted in a significant reduction in tensile strength at maximum. However, after UV irradiation, significant increases in both the strain at break and strength at maximum were only observed in 1% ZnO/TMSC-protected papers. Regarding their anti-fungal properties, the 1% ZnO/TMSC films were effective in growth inhibitions of Aspergillus sp. and Penicillium sp. on the nonirradiated papers. Despite being hydrophilic after UV-irradiation, growths of the molds were severely suppressed on the UV-irradiated paper. [ABSTRACT FROM AUTHOR]

Time series analysis predicts the future based on existing historical data and has a wide range of applications in finance, economics, meteorology, biology, engineering, and other fields. Although the combination of decomposition techniques and machine learning algorithms can effectively solve the problem of predicting nonstationary sequences, this kind of decomposition-integration-prediction strategy of the prediction method has serious defects. After the decomposition of the division of the training set and the test set, the information of the test set in the process of decomposition of the information leakage ultimately shows a high accuracy of the prediction of the illusionary. This paper proposes three improvement strategies for this type of "information leakage" problem: sliding window decomposition (SW-EMD), single training and multiple decomposition (STMP-EMD), and multiple training and multiple decomposition (MTMP-EMD). They are combined with a bidirectional multiscale temporal convolutional network (MSBTCN), bidirectional long- and short-term memory network (BiLSTM), and attention mechanism (DMAttention), which introduces a dependency matrix based on cosine similarity to be applied to water quality prediction. The experimental results show that the model achieves good performance in the prediction of three water quality indicators (pH, DO and KMnO4), and the accuracies of the three models proposed in this paper are improved by 1.958% and 0.853% in terms of the RMSE and MAPE, respectively, compared with those of the mainstream LSTM models. The key contributions of this study include the following: (1) three methods are proposed to improve the class EMD decomposition, which can effectively solve the problem of "information leakage" that exists in the current models via class EMD decomposition; (2) the CEEMDAN-MSBTCN-BiLSTM-DMAttention model structure is innovated by combining improved class EMD decomposition methods; and (3) the three improved decomposition methods proposed in this paper can effectively solve the problem of "information leakage" and optimize the prediction model at the same time. This study provides an effective experimental method for water quality prediction and can effectively address the problem of "overfitting" models via class EMD decompositions during model training and testing. [ABSTRACT FROM AUTHOR]

In this paper, three kinds of micro-nano bamboo powder (MBP) and alkyl ketene dimer (AKD) were added to the polyvinyl alcohol/cellulose nanofiber (PVA/CNF) coating to prepare PVA/CNF/MBP coated paper and PVA/CNF/M-MBP/AKD coated paper. The results showed that MBP improved the oleophobicity of PVA/CNF coating, and the grease resistance grade of PVA/CNF/B-MBP and PVA/CNF/M-MBP coated papers reached the highest level, with a kit number of 12. Among the PVA/CNF/MBP coated papers, the PVA/CNF/M-MBP coated paper has the best hydrophobic properties, with the water contact angle and Cobb value of 74° and 21.3 g/m2, respectively. In addition, when the AKD dosage was 0.2% in the PVA/CNF/M-MBP/AKD coating, the kit number of the coated paper was 11, the Cobb value was 15.2 g/m2, the water contact angle was 103°, and the tensile strength was found to increase slightly. Therefore, compared with PVA/CNF coated paper, PVA/CNF/M-MBP/AKD coated paper has good strength and excellent hydrophobic and oleophobic properties. [ABSTRACT FROM AUTHOR]

The valorization of paper mill sludge (PMS) is the main goal of this study. The emissions of PMS continue to increase at global scale, especially from packaging paper and board sectors. The raw sludge was used to prepare an adsorbent to remove toxic pollutants from wastewater, the methylene blue (MB), an organic dye. Firstly, the physico-chemical characterization of PMS was done determining the crystalline phases of PMS fibers, the content of main elements, and the pH zero point charge, which was determined at around pH 7. The adsorption of MB on PMS powder was studied at 18 °C with an agitation of 200 rpm, being the best operating conditions 30 min of contact time, 250 mg L−1 of initial MB concentration and 0.05 g in 25 mL of adsorbent dose. Experimental data of MB adsorption was fitted to Langmuir and Freundlich isotherm equations. The Langmuir model was more accurate for the equilibrium data of MB adsorption at pH 5.1. The PFOM and PSOM were adjusted to experimental adsorption kinetics data, being PSOM, which describes better the MB adsorption by PMS powder. This was confirmed by calculating the maximum adsorption capacity with PSOM, which was 42.7 mg g−1, being nearly similar of the experimental value of 43.5 mg g−1. The analysis of adsorption thermodynamics showed that the MB was adsorbed exothermically with a ΔH0 = − 20.78 kJ mol−1, and spontaneously with ΔG0 from − 0.99 to − 6.38 kJ mol−1 in the range of temperature from 291 to 363 K, respectively. These results confirm that the sludge from paper industry can be used as biosorbent with remarkable adsorption capacity and low cost for the treatment of wastewater. PMS can be applied in the future for the depollution of the effluents from the textile industry, which are highly charged with dyes. [ABSTRACT FROM AUTHOR]

To achieve integrated resource utilization of graphite tailings to improve their water-holding capacity, river silt and cow dung powder were added to graphite tailings as organic matter improvers. Improver ratios were designed using 4 g cow dung powder and 20, 30, and 50 g river silt. Soil–water characterization tests were performed using a combined tensiometer and filter paper method based on optimum density measurements. Analysis of the influence of river silt dosing on the soil–water characteristic curves of improved graphite tailing specimens was performed with data fitting using the Van Genuchten model. Here, we investigated the effect of river silt dosing on the internal pore structure and water-holding capacity of modified graphite tailing samples and verified the applicability of the model to graphite tailings. Our results demonstrate that the organic matter improver incorporated into graphite tailings can improve the internal structural compactness of graphite tailings, improving the water holding capacity. With an increase in river silt dosage, the saturated water content is larger, and the residual water content increases and then decreases. When river silt dosage is 30 g, the residual water content is the highest at a value of 3.32%. The van Genuchten model was highly accurate for assessing the graphite tailings. With an increase in river silt doping, the internal pore space first decreased and then increased, and the internal structure gradually became compact and loosened. The internal structure was in the optimal state in the experimental study when the dosage of cow dung powder was 4 g and the dosage of river silt was 30 g. The water holding capacity was optimal at this time. The results of this study provide a theoretical foundation for graphite-tailing-based mine reclamation and play a guiding role in exploring the value of the hydraulic characteristic index parameters when applying graphite tailings engineering. [ABSTRACT FROM AUTHOR]

Paper and packaging materials a lignocellulose-based natural biodegradable polymer that spontaneously releases acetic acid, aldehydes, alcohol, and ester-based volatile organic compounds (VOCs) upon ageing and these VOCs start degrading the paper products and decline their mechanical strength properties. The reactivity of the paper of unbleached wheat straw pulp towards acetic acid and hexanal, which has been proven to have more degrading effects on paper than other VOCs, was considered in this work. The papers were exposed to these volatile compounds for 90 days in an air-tight vessel under ambient environmental conditions. The results showed that hexanal was more destructive than acetic acid with regards to cellulose degradation and depletion in the mechanical strength properties. The paper properties like, tensile, tear and burst index, viscosity, pH and carbonyl group content was measured. The growth of the carbonyl group, evidence of the ageing effects in the paper, detected more in the paper exposed to acetic acid. However, the strength of paper properties declined more with hexanal. FE-SEM analysis of the sample showed the development of pores and damage of cellulose fibre upon ageing. Similarly, the damaging effects of VOCs on cellulose, hemicelluloses and lignin were confirmed by significantly reduced peak detection through FT-IR \analysis. The high crystallinity index of the paper products due to exposure to VOCs was detected by XRD analysis, which confirmed the degradation of the low molecular weight cellulose molecule. Thus, the results are strongly recommended that VOCs that generates due to natural or artificial ageing could be the leading cause of paper degradation. [ABSTRACT FROM AUTHOR]

This paper focuses on the online anti-epidemic resource allocation between demanders and suppliers considering the epidemic spatial spread. The spatial crowdsourcing with sharing platform is an effective way for anti-epidemic resource allocation, and a reasonable online matching strategy can improve the efficiency of resource utilization. The paper proposes online matching heuristic strategy (HSTRF-LRLUF strategy) and designs an online batch bilateral matching algorithm for anti-epidemic resources, which considers the impact of grid spatial aggregation and diffusion risk of emerging infectious diseases. The population distribution within grids and the commuting patterns between grids can provide decision support for selecting online matching strategies of anti-epidemic resources. A larger matching time window focusing on the spatial transmission risk (TR) of the epidemic can obtain better matching results. However, with a smaller matching time window, the decision makers can focus on spatial agglomeration risk (OR) or spatial diffusion risk (IR). The paper effectively combines the spatial crowdsourcing model with the anti-epidemic resource allocation to achieve the allocation of emergency resources to individuals. A combined anti-epidemic resource online matching heuristic strategies is designed from the spatial agglomeration risk and the spatial diffusion risk. Decision makers can dynamically adjust the online matching strategies of anti-epidemic resources by evaluating the spatial agglomeration risk, the spatial diffusion risk, and the overall spatial transmission risk based on the real-time spread of the epidemic and the supply of anti-epidemic resources. [ABSTRACT FROM AUTHOR]

For shaped charge blasting projects in mining, civil engineering, and similar fields, it is proposed to modify the charge structure by combining slotted tubes and shaped charge liners to obtain a new type of charge structure. This aims to achieve directional rock breaking through the focused action of the shaped charge. The influence of different slotted pipe materials on the directional rock-breaking effect of concentrated energy using a new charge structure is explored through theoretical analysis combined with model test study, high-speed camera, stress–strain gauge, and other equipment. A comparison is made between slotted pipes made of aluminum, kraft paper, and PVC, with the cutting width of 2 mm. Based on the characteristics of the cracks formed after blasting, the new charge structure made of aluminum slotted pipe produces a penetrating crack that is almost consistent with the pre-cracking direction. Based on the corresponding characteristics of successively released blasting energy, the guiding and convergence effect of the new charge structure made of aluminum slotted pipe on the explosion energy is greater than that of the new charge structure made of the other two types of slotted pipe material. According to the strain data measured after blasting, the peak arrival time of the strain peak in the direction of the slotted pipe on one side of the shaped hood is shorter than that in the other two directions, and the peak strain is greater than that in the other two directions while having a better energy gathering effect. Based on the findings, the new charge structure with directional energy concentration has a damage reduction effect. Furthermore, the material of aluminum slotted pipe is found to be better than PVC slotted pipe, whereas the material of PVC slotted pipe is better than kraft paper slotted pipe in achieving directional rock breaking. [ABSTRACT FROM AUTHOR]

Rapid and accurate bioburden detection has become increasingly necessary for food, health, pharmaceutical and environmental applications. To detect bioburden accurately, and in a highly sensitive manner, we have fabricated a novel microfluidic device with an integrated filter to trap the cells. Bioburden is detected on the filter paper in situ using the redox reaction of fluorescent label resorufin and a portable multichannel fluorometer is used for fluorescence measurement. The microfluidic device was fabricated in a facile, low-cost, and rapid way with microwave-induced thermally assisted bonding. To characterize the bonding quality of the microfluidic cassettes, different tests were performed, and the filter paper material and size were optimized. Primary Bacillus subtilis culture bacterial samples were filtered through the device to validate and investigate the performance parameters. Our results show that a limit of detection (LOD) of 0.037 CFU/mL can be achieved through this microfluidic device whereas the LOD in a normal microfluidic cassette in the fluorometer and the golden standard spectrophotometer are 0.378 and 0.128 CFU/mL respectively. The results depict that three to ten times LOD improvement is possible through this microfluidic cassette and more sensitive detection is possible depending on the volume filtered within a rapid 3 min. This novel microfluidic device along with the fluorometer can be used as a rapid portable tool for highly sensitive, accurate and high-throughput bacterial detection for different applications. [ABSTRACT FROM AUTHOR]

Laserjet printing is a kind of facile and digital do-it-yourself strategies, which is of importance to fabricate inexpensive paper-based microfluidic devices. However, the printed hydrophobic barrier is not hydrophobic enough due to the weak hydrophobicity and requires subsequent heating, which can lead to the pyrolysis of cellulose in the paper and influence the detection results. Here, for the first time, we report a kind of functional toner including toner and polydopamine (PDA) nanocapsules which contains oleic acid modified ferric tetroxide (OA-Fe3O4) and octadecylamine (ODA), which is suitable for printing with desired shapes and sizes to lead to formation of superhydrophobic barriers. Moreover, patterns printed with functional toner have good stability, including resistance to moisture, ultraviolet (UV) and bending. Finally, a proof-of-concept of metal and nitrite ions testing is demonstrated using colorimetric analysis, and the results show that the printed devices successfully perform instant detection of ions. The developed functional toner offers easy fabrication, cost-effectiveness and mass production of paper-based devices. In general, this strategy provides a new idea and technical support for the rapid prototyping of microfluidic paper-based analytical devices (μPADs) using laserjet printing. [ABSTRACT FROM AUTHOR]

The valorization of paper mill sludge (PMS) is the main goal of this study. The emissions of PMS continue to increase at global scale, especially from packaging paper and board sectors. The raw sludge was used to prepare an adsorbent to remove toxic pollutants from wastewater, the methylene blue (MB), an organic dye. Firstly, the physico-chemical characterization of PMS was done determining the crystalline phases of PMS fibers, the content of main elements, and the pH zero point charge, which was determined at around pH 7. The adsorption of MB on PMS powder was studied at 18 °C with an agitation of 200 rpm, being the best operating conditions 30 min of contact time, 250 mg L−1 of initial MB concentration and 0.05 g in 25 mL of adsorbent dose. Experimental data of MB adsorption was fitted to Langmuir and Freundlich isotherm equations. The Langmuir model was more accurate for the equilibrium data of MB adsorption at pH 5.1. The PFOM and PSOM were adjusted to experimental adsorption kinetics data, being PSOM, which describes better the MB adsorption by PMS powder. This was confirmed by calculating the maximum adsorption capacity with PSOM, which was 42.7 mg g−1, being nearly similar of the experimental value of 43.5 mg g−1. The analysis of adsorption thermodynamics showed that the MB was adsorbed exothermically with a ΔH0 = − 20.78 kJ mol−1, and spontaneously with ΔG0 from − 0.99 to − 6.38 kJ mol−1 in the range of temperature from 291 to 363 K, respectively. These results confirm that the sludge from paper industry can be used as biosorbent with remarkable adsorption capacity and low cost for the treatment of wastewater. PMS can be applied in the future for the depollution of the effluents from the textile industry, which are highly charged with dyes. [ABSTRACT FROM AUTHOR]

The agricultural development in China is currently grappling with the challenges of limited water and soil resources, environmental pollution, and ecosystem degradation. Therefore, improving agricultural green productivity has become the focus of academic attention. Based on the panel data of 30 provinces in China from 2008 to 2020, this paper constructs an index system of agricultural productivity. Subsequently, the super-efficiency SBM model is used to calculate the green productivity of agriculture, and its characteristics are analyzed from the perspectives of temporal and spatial.Through the empirical test of threshold model, it is found that China's agricultural green productivity shows a gradual growth trend from 2008 to 2020, and the growth rate has accelerated significantly in recent years. There is a non-linear relationship between energy structure and agricultural green productivity. Especially in areas with reasonable energy structure, the increase in the proportion of coal consumption will inhibit the improvement of green agricultural productivity. This paper suggests reducing dependence on fossil energy, improving market mechanism and optimizing resource utilization in order to promote green agricultural production in China. This study expands the research perspective of agricultural green productivity, provides new research methods and ideas for related fields, and provides a reasonable energy allocation plan for agricultural production, which helps to improve production efficiency and reduce costs. [ABSTRACT FROM AUTHOR]

Failure Modes, Effects, and Criticality Analysis (FMECA) is a commonly used method for analyzing system reliability. It is frequently applied in identifying weak points in the reliability of CNC machine tools. However, traditional FMECA has issues such as vague descriptions of risk factors, equal treatment of risk factors, and unclear directions for improving weak points. In response to the issue of vague descriptions of risk factors, this paper further expands severity (S) into machine hazard (M) and personal hazard (P), and subdivides detectability (D) into functional structural complexity (D1) and detection cost (D2). In addressing the issue of treating risk factors equally, this paper integrates Distance Analysis Method (DAM) and Grey Relational Analysis (GRA) to propose Distance-Grey Relational Analysis (D-GRA). Subsequently, based on the D-GRA method, the weights of each risk factor were determined by comprehensively considering expert system scores and actual economic loss indicators. In response to the issue of unclear improvement directions for weak points, this paper introduces the BCC model. It treats common failure modes of CNC machine tools as decision-making units within the BCC model, refines risk factors as input indicators, and evaluates the efficiency values of each decision-making unit based on various actual losses as output indicators. Through efficiency value analysis, it proposes improvement directions for weak points. Then, based on the weights of risk factors and the efficiency values of failure modes, a modified calculation method for the new Risk Priority Number (RPN) is proposed to amend the traditional RPN, This paper takes the electric spindle system of a certain machining center as an example, applies the proposed method to rank common failure modes with the new RPN, and compares it with other RPN calculation methods to verify the rationality of the proposed approach. Finally, it presents improvement directions for reliability enhancement. [ABSTRACT FROM AUTHOR]

Reflecting sex and gender characteristics in biomedical research is critical to improving health outcomes and reducing adverse effects from medical treatments. This study investigates the impact of sex/gender-specific funding policies and journal editorial standards on the integration of sex/gender analysis in biomedical research publications. Using data from the United States, Canada, the United Kingdom, and other countries between 2000 and 2021, we assessed how these policies influenced research output in the fields of medicine and life sciences. Our findings show that countries with progressive funding policies and journals promoting sex/gender-based reporting have significantly improved research quality and publication rates. This highlights the importance of coordinated policy efforts and editorial practices in advancing integrated sex/gender research. We recommend continued global efforts from policymakers, funding bodies, and journals to embed sex/gender perspectives in scientific inquiry, ensuring more effective and equitable biomedical advancements. [ABSTRACT FROM AUTHOR]

Bridges are vital assets of transport infrastructure, systems, and communities. Damage characterization is critical in ensuring safety and planning adaptation measures. Nondestructive methods offer an efficient means towards assessing the condition of bridges, without causing harm or disruption to transport services, and these can deploy measurable evidence of bridge deterioration, e.g., deflections due to tendon loss. This paper presents an enhanced input-doubling technique and the Artificial Neural Network (ANN)-based cascade ensemble method for bridge damage state identification and is exclusively relying on small datasets, that are common in structural assessments. A new data augmentation scheme rooted in the principles of linearizing response surfaces is introduced, which significantly boosts the efficiency of intelligent data analysis when faced with limited volumes of data. Furthermore, improvements to a two-step ANN-based ensemble method, designed for solving the stated task, are presented. By adding the improved input-doubling methods as simple predictors in the first part of the cascade ensemble and optimizing it, we significantly boost accuracy (7%, 0.5%, and 8% based on R2 in predicting tendon losses for three critical zones that were defined across the deck of a real deteriorated prestressed balanced cantilever bridge). This improvement is strong evidence of the accuracy of the proposed method for the task at hand that is proven to be more accurate than other methods available in the international literature. [ABSTRACT FROM AUTHOR]

Identifying the ash accumulation generated on the water-cooled walls of the waste incinerator is essential for the cleanup by the robotic arm. This paper improves a new algorithm based on YOLOv8n, which can identify the ash accumulation position on the water-cooled wall quickly and accurately. Firstly, the multi-scale fusion image enhancement algorithm is used to improve the sharpness and contrast of the image and enrich the details of the image. Secondly, the backbone feature extraction network of YOLOv8n is replaced by Mobilenetv3 network, which reduces the parameters in the model greatly. Finally, this paper improves a new attention mechanism AWGAM (Add Weight Global Attention Mechanism) based on GAM (Global Attention Mechanism), which can better integrate the feature information between different dimensions and improve the learning ability of the model. AWGAM is added to the backbone of the model. The experimental results show that compared with the original YOLOv8n model, the improved YOLOv8n model has 59.9% fewer parameters, 4.4% higher precision, 8.8% higher recall, 3.2% higher mAP50 (mean Average Precision) and 8.8% higher mAP50-95. This model has made remarkable progress on the basis of the original algorithm, and has strong competitiveness compared with other advanced target detection models. The lightweight and high accuracy of ash accumulation detection offered by the proposed model presents promising applications in ash accumulation detection tasks of water-cooled walls. [ABSTRACT FROM AUTHOR]

Paper coating plays an important role in the paper properties, printability and application. The nanocoating is a multifunction layer that provides the paper with unique features. In this work, nanocoating formulas were prepared using a green method and component. The nanocoating formulas were based on biopolymers nanostarch NSt and nanochitosan NCh (NCS) decorated with Egyptian kaolinite Ka doped with zinc nanoparticles NCS@xka/ZnONPs (x represents different ratios) support for multifunctional uses. The nanocoating formulas were characterized using a physiochemical analysis as well as a topographical study. FTIR, XRD, SEM and TEM techniques were used. Additionally, the antimicrobial activity of the tested samples was assessed against six microorganisms including Gram-negative and Gram-positive bacteria. The prepared nanocoating formulas affirmed excellent antimicrobial activity as a broad-spectrum antimicrobial active agent with excellent activity against all representative microbial communities. The nanocoating with the highest ratio of Ka/ZnONPs (NCS@40 ka/ZnONPs) showed excellent antimicrobial activity with an inhibition percentage of more than 70% versus all microorganisms presented. The paper was coated with the prepared suspensions and characterized concerning optical, mechanical and physical properties. When Ka/ZnONPs were loaded into NCS in a variety of ratios, the characteristics of coated paper were enhanced compared to blank paper. The sample NCS@40 ka/ZnONPs increased tensile strength by 11%, reduced light scattering by 12%, and improved brightness and whiteness by 1%. Paper coated with NCh suspension had 35.32% less roughness and 188.6% less porosity. When coated with the sample NCS@10 ka/ZnONPs, the coated paper's porosity was reduced by 94% and its roughness was reduced by 10.85%. The greatest reduction in water absorptivity was attained by coating with the same sample, with a reduction percentage of 132%. [ABSTRACT FROM AUTHOR]

Paper coating plays an important role in the paper properties, printability and application. The nanocoating is a multifunction layer that provides the paper with unique features. In this work, nanocoating formulas were prepared using a green method and component. The nanocoating formulas were based on biopolymers nanostarch NSt and nanochitosan NCh (NCS) decorated with Egyptian kaolinite Ka doped with zinc nanoparticles NCS@xka/ZnONPs (x represents different ratios) support for multifunctional uses. The nanocoating formulas were characterized using a physiochemical analysis as well as a topographical study. FTIR, XRD, SEM and TEM techniques were used. Additionally, the antimicrobial activity of the tested samples was assessed against six microorganisms including Gram-negative and Gram-positive bacteria. The prepared nanocoating formulas affirmed excellent antimicrobial activity as a broad-spectrum antimicrobial active agent with excellent activity against all representative microbial communities. The nanocoating with the highest ratio of Ka/ZnONPs (NCS@40 ka/ZnONPs) showed excellent antimicrobial activity with an inhibition percentage of more than 70% versus all microorganisms presented. The paper was coated with the prepared suspensions and characterized concerning optical, mechanical and physical properties. When Ka/ZnONPs were loaded into NCS in a variety of ratios, the characteristics of coated paper were enhanced compared to blank paper. The sample NCS@40 ka/ZnONPs increased tensile strength by 11%, reduced light scattering by 12%, and improved brightness and whiteness by 1%. Paper coated with NCh suspension had 35.32% less roughness and 188.6% less porosity. When coated with the sample NCS@10 ka/ZnONPs, the coated paper's porosity was reduced by 94% and its roughness was reduced by 10.85%. The greatest reduction in water absorptivity was attained by coating with the same sample, with a reduction percentage of 132%. [ABSTRACT FROM AUTHOR]

Energy storage devices (ESD) which are intended to power electronic devices, used in close contact of human skin, are desirable to be safe and non-toxic. In light of this requirement, Zn based energy storage devices seem to provide a viable pathway as they mostly employ aqueous based electrolytes which are safe and non-toxic in their functioning. Additionally, having a flexible ESD will play a crucial role as it will enable the ESD to conform to the varying shapes and sizes of wearable electronics which they energize. In this work, we have developed an inkjet-printed Zinc ion battery (IPZIB) with planar electrode configuration over bond paper substrate. Zn has been used as the negative electrode, MnO2 is used as the positive electrode with Poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) as the active binder. Conducting tracks of reduced graphene oxide (rGO) are used to construct the current collector on the paper substrate. The fabricated IPZIB delivered a high discharge capacity of 300.14 mAh g−1 at a current density of 200 mA g−1. The energy density of the IPZIB is observed as 330.15 Wh kg−1 at a power density of 220 W kg−1 and retains an energy density of 94.36 Wh kg−1 at a high power density of 1650 W kg−1. Finally, we have demonstrated the capability of the IPZIB to power a LED at various bending and folding conditions which indicates its potential to be used in the next generation flexible and wearable electronic devices. [ABSTRACT FROM AUTHOR]

Rapid and accurate bioburden detection has become increasingly necessary for food, health, pharmaceutical and environmental applications. To detect bioburden accurately, and in a highly sensitive manner, we have fabricated a novel microfluidic device with an integrated filter to trap the cells. Bioburden is detected on the filter paper in situ using the redox reaction of fluorescent label resorufin and a portable multichannel fluorometer is used for fluorescence measurement. The microfluidic device was fabricated in a facile, low-cost, and rapid way with microwave-induced thermally assisted bonding. To characterize the bonding quality of the microfluidic cassettes, different tests were performed, and the filter paper material and size were optimized. Primary Bacillus subtilis culture bacterial samples were filtered through the device to validate and investigate the performance parameters. Our results show that a limit of detection (LOD) of 0.037 CFU/mL can be achieved through this microfluidic device whereas the LOD in a normal microfluidic cassette in the fluorometer and the golden standard spectrophotometer are 0.378 and 0.128 CFU/mL respectively. The results depict that three to ten times LOD improvement is possible through this microfluidic cassette and more sensitive detection is possible depending on the volume filtered within a rapid 3 min. This novel microfluidic device along with the fluorometer can be used as a rapid portable tool for highly sensitive, accurate and high-throughput bacterial detection for different applications. [ABSTRACT FROM AUTHOR]

Rapid and accurate bioburden detection has become increasingly necessary for food, health, pharmaceutical and environmental applications. To detect bioburden accurately, and in a highly sensitive manner, we have fabricated a novel microfluidic device with an integrated filter to trap the cells. Bioburden is detected on the filter paper in situ using the redox reaction of fluorescent label resorufin and a portable multichannel fluorometer is used for fluorescence measurement. The microfluidic device was fabricated in a facile, low-cost, and rapid way with microwave-induced thermally assisted bonding. To characterize the bonding quality of the microfluidic cassettes, different tests were performed, and the filter paper material and size were optimized. Primary Bacillus subtilis culture bacterial samples were filtered through the device to validate and investigate the performance parameters. Our results show that a limit of detection (LOD) of 0.037 CFU/mL can be achieved through this microfluidic device whereas the LOD in a normal microfluidic cassette in the fluorometer and the golden standard spectrophotometer are 0.378 and 0.128 CFU/mL respectively. The results depict that three to ten times LOD improvement is possible through this microfluidic cassette and more sensitive detection is possible depending on the volume filtered within a rapid 3 min. This novel microfluidic device along with the fluorometer can be used as a rapid portable tool for highly sensitive, accurate and high-throughput bacterial detection for different applications. [ABSTRACT FROM AUTHOR]

Pharmacists are expected to demonstrate their expertise in clinical practice and conduct research activities to generate new evidence. However, the factors promoting research activities among pharmacists remain unclear. Therefore, we investigated the research activities of Japanese pharmacists through a questionnaire survey and examined the factors contributing to the promotion of research activities. A web-based questionnaire using Google Forms was disseminated across pharmacists working in community pharmacies, drugstores, hospitals, and clinics. The questionnaire included respondents' backgrounds, research activities, and research environments. Logistic regression analysis was used to examine the factors promoting pharmacists' research activities, with experience in research paper acceptance as the objective variable. In total, 401 responses were included in the analysis. Of the respondents, 54.1% were hospital pharmacists, and 77.1% were pharmacists with > 5 years of pharmacist experience. Furthermore, 50.4% of the pharmacists had presented at conferences, and 22.2% had experience in research paper acceptance. The influential factors were "master's degree or higher," "number of affiliated academic societies," "acquisition of specialists/certified pharmacists," and "daily availability of a consultant for writing research papers." This study revealed the factors contributing to the promotion of research activities among pharmacists. We believe that our findings will help promote research among pharmacists. [ABSTRACT FROM AUTHOR]

As the social organism, Polistes wasps build a communal nest using woody fibers with saliva for sustaining brood and adult population throughout the season. Limited information exists regarding the identification specific plant materials employed in wasp nest building. Thus, we firstly tested if the DNA metabarcoding approach utilizing rbcL and trnL molecular markers could identify the plant species quantitatively and qualitatively inform the mixed-origin woody samples. A threshold of 0.01 proportion of reads was applied for rbcL and trnL molecular markers, while this threshold for median proportion was 0.0025. In assessing taxa richness, the median proportion demonstrated superior performance, exhibiting higher taxa detection power, however, rbcL marker outperformed in quantitative analysis. Subsequently, we applied DNA metabarcoding to identify the plant materials from the nests of two Polistes species, P. mandarinus and P. rothneyi. The results showed that higher preference of Quercus and Robinia as the major nest building materials regardless of the surrounding plant communities, by two wasp species. Material diversity was higher for P. rothneyi than P. mandarinus, which may explain the abundance of this species possibly with heightened adaptive capacities in their nesting behavior. This study demonstrated that DNA metabarcoding could identify the complex nest-building plant materials of paper wasps and provide insights into their ecological interactions in the natural ecosystem. [ABSTRACT FROM AUTHOR]

In this work heat transfer papers were loaded with a new core–shell pigment based on precipitating thin shell of titanium dioxide on a core of rice husk silica ash TiO2/RHSA to be applied in dye sublimation printing of textile fabrics. Besides, 0.1% (w/w) cationic polyacrylamide (CPAM) and 1% (w/w) bentonite (Bt) were also added sequentially to improve drainage and filler retention of the paper hand-sheets made from bleached kraft bagasse pulps. The effect of the new core–shell pigment on the mechanical and barrier properties, thermal stability and surface morphology of modified paper sheets were investigated. In addition, the study of transfer printability and ease of dye release from paper to fabric in this heat transfer printing of polyester fabrics using silk-screen printing under different transfer parameters were studied. Also, fastness measurements including washing, light and perspiration of printing polyester fabric were also estimated. [ABSTRACT FROM AUTHOR]

The welding workshop of metal structural parts is highly energy-consuming. To meet the national low-carbon green demand, this paper focus on the welding workshop scheduling problem in production process with considering the carbon footprints such as equipment energy consumption, welding material consumption and shielding gas consumption. Firstly, a bi-objective low-carbon welding scheduling mathematical model is established with minimizing makespan and carbon emission. Then, an improved Grey Wolf Optimizer (IGWO) with three strategies is designed to solve this multi-objective problem. The grey wolf multi-wandering strategy (first) is proposed to enhance the population diversity. The grey wolf coordinated hunting strategy (second) based on dynamic weights is introduced to improve the convergence of IGWO. A local optimization strategy(third) is designed to improve the post-optimal search performance by adjusting the machine assignment based on the critical path. A welding workshop green scheduling case is designed to verify the model and algorithm proposed in this paper. The minimum completion time and carbon emissions obtained by the IGWO algorithm are 842.14 and 3.85E + 05, respectively. This result is better than that obtained by NSGA-II and GWO.The results show that the model effectively reduce the carbon emissions of the workshop, and the algorithm can effectively solve the model. [ABSTRACT FROM AUTHOR]

Synthetic aperture radar (SAR) is crucial for military reconnaissance and remote sensing, but image quality can be affected by various factors, impacting target detection performance. Thus, pre-evaluation of SAR image quality is essential to filter out poor-quality images, optimize resource allocation, and enhance detection accuracy and efficiency. This paper proposes a comprehensive SAR image quality evaluation method combining objective and subjective approaches. Specifically, the processes encompassing the generation of a series of disturbed SAR images on the SAR ship detection dataset (SSDD), the calculation of various objective quality indicators for those images, and the assignment of a subjective quality label to each image through subjective evaluation. Based on the dataset constructed by the above evaluation methods, the IHHO-XGBoost model was developed. This model uses an improved harris hawk optimization (IHHO) algorithm to optimize extreme gradient boosting (XGBoost) hyperparameters. The IHHO algorithm effectively alleviates the problem of getting trapped in local optima by improving the escape energy calculation strategy and integrating the average difference evolution mechanism while maintaining the diversity of the population, showing significant advantages over the traditional HHO algorithm. Comparative experiments demonstrate the model's superiority in SAR image quality evaluation. This study validates the scientificity and practicability of the proposed method, offering new tools for SAR image quality research. [ABSTRACT FROM AUTHOR]

Underwater target detection technology is very important for Marine resources detection and underwater environment perception. The problems of low-quality underwater images, a large amount of calculation, and low accuracy of target detection models still need to be solved. Firstly, a new underwater image enhancement algorithm based on multi-scale fusion is proposed. The algorithm combines the improved white balance algorithm and the improved CLAHE (Contrast Limited Adaptive Histogram Equalization) and realizes the multi-scale fusion strategy by introducing different weight maps, aiming to improve the visual effect and quality of underwater images. Secondly, to further improve the accuracy and efficiency of underwater target detection, an improved YOLOv5s lightweight underwater target detection algorithm is proposed. The algorithm combines the Ghost convolution module, EMA(Efficient Multi-Scale Attention) mechanism, and CARAFE (Content-Aware ReAssembly of FEatures) up-sampling mode. The comparison on the URPC(Underwater Robot Perception Challenge) public dataset shows that the proposed algorithm has achieved significant improvement in terms of model size, parameter amount, calculation amount, and mAP@0.5. Thirdly, to verify the effectiveness of the image enhancement algorithm and underwater target detection algorithm proposed in this paper, the ROV(Remote Operated Vehicle) is used to conduct experiments in the experimental pool. By designing underwater target detection experiments before and after image enhancement, the results show that the enhanced image significantly improves the detection ability of underwater targets. Finally, underwater target detection software is developed to provide strong support for the application of underwater-related fields. [ABSTRACT FROM AUTHOR]

Efficient prediction of blastocyst formation from early-stage human embryos is imperative for improving the success rates of assisted reproductive technology (ART). Clinics transfer embryos at the blastocyst stage on Day-5 but Day-3 embryo transfer offers the advantage of a shorter culture duration, which reduces exposure to laboratory conditions, potentially enhancing embryonic development within a more conducive uterine environment and improving the likelihood of successful pregnancies. In this paper, we present a novel ResNet-GRU deep-learning model to predict blastocyst formation at 72 HPI. The model considers the time-lapse images from the incubator from Day 0 to Day 3. The model predicts blastocyst formation with a validation accuracy of 93% from the cleavage stage. The sensitivity and specificity are 0.97 and 0.77 respectively. The deep learning model presented in this paper will assist the embryologist in identifying the best embryo to transfer at Day 3, leading to improved patient outcomes and pregnancy rates in ART. [ABSTRACT FROM AUTHOR]

The rapid advancement of artificial intelligence and robot technology has spurred the proposal and innovation of a coal gangue sorting robot system (CGSRS) paradigm. The time-varying raw coal flow (TVRCF) with multi-scene and full working conditions affects the gangue queue. Configuring the CGSRS scheme correctly is combative. The field environment puts forward higher requirements for the time complexity of the CGSRS multi-task allocation strategy. Therefore, this paper proposes a scheme evaluation method of the CGSRS with time-varying multi-scenario based on deep learning. Firstly, the gangue queue data set of multi-scene and full-condition TVRCF was obtained according to the belt speed, the maximum coal flow, and the uncorrelated nonlinear changes of coal flow and gangue content. The CGSRS scheme is established based on robot number and rule combination, and the multi-task allocation strategy is adjusted to generate the labels of the gangue queue. Then, the RGB sample set is established based on the labels of the gangue queue. The CGSRS scheme evaluation model is trained based on DenseNet. Finally, the CGSRS scheme evaluation method was designed to realize the prediction of a random gangue queue. In this paper, the CGSRS scheme evaluation model, the stability of the solution, and the comparison of methods are carried out. Experimental results show that the solution of the CGSRS scheme evaluation model is accurate and stable. The time complexity is significantly reduced and very stable. The CGSRS scheme evaluation method is applied to the CGSRS multi-task allocation problem, and the stability of the solution is not affected by the data. It is significantly better than the multi-task allocation strategy. The proposed method is the first attempt to apply deep learning to a multi-task allocation problem in CGSRS. [ABSTRACT FROM AUTHOR]

The goal of the paper is to examine how convolutional neural network (CNN) is used in the immersive world of digital media art. In order to do this, this paper first explains digital media art in the context of smart cities and the use of immersive scenarios. Next, a brief analysis of the Unet network model and deep aggregation structure is provided. Then, a projector, camera, and computer-based immersive projector-camera display system is constructed. Based on the mathematical reflection model of the system, this paper discusses the method of using CNN to solve the photometric compensation of the projection picture. Meanwhile, a Projection Compensation Network (PCN) is designed, and a multi-scale perceptual loss is added to this compensation network, and the content information of the compensated image is improved by calculating the loss of feature maps of different scales. The final network is named Perceptual Loss-Projection Compensation Network (PL-PCN). Experiments are used to confirm the PL-PCN model's efficacy. The outcomes demonstrate that the SSIM and PSNR of the projected picture compensated by PL-PCN are boosted by 35.8% and 31.6%, respectively. While the RMSE is reduced by 40.9%, demonstrating an improvement in the compensated image's quality. Additionally, utilizing a CNN makes it possible to do cross-reflection compensation. Additionally, compared to the network without deep polymerization, the PL-PCN with deep polymerization structure boosts the projected image's SSIM and PSNR by 6% and 7.57%, respectively, and lowers the RMSE by 13.3% This demonstrates that the addition of deep polymerization structure can have a stronger compensatory effect. This paper can offer a theoretical framework for improving the immersive scene quality of digital media art. [ABSTRACT FROM AUTHOR]

To tackle the challenge of low accuracy in stock prediction within high-noise environments, this paper innovatively introduces the CED-PSO-StockNet time series model. Initially, the model decomposes raw stock data using the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) technique and reconstructs the components by estimating their frequencies via the extreme point method. This process enhances component stability and mitigates noise interference. Subsequently, an Encoder-Decoder framework equipped with an attention mechanism is employed for precise prediction of the reconstructed components, facilitating more effective extraction and utilization of data features. Furthermore, this paper utilizes an Improved Particle Swarm Optimization (IPSO) algorithm to optimize the model parameters. On the Pudong Bank dataset, through ablation experiments and comparisons with baseline models, various optimization strategies incorporated into the proposed CED-PSO-StockNet model were effectively validated. Compared to the standalone LSTM model, CED-PSO-StockNet achieved a remarkable 45.59% improvement in the R2 metric. To further assess the model's generalization capability, this paper also conducted comparative experiments on the Ping An Bank dataset, and the results underscored the significant advantages of CED-PSO-StockNet in the domain of stock prediction. [ABSTRACT FROM AUTHOR]

A growing concern is that as local newspapers disappear, communities lose trusted gatekeepers and develop information voids, creating openings for misinformation to thrive. Previous work has not evaluated whether residents of news deserts have developed different information acquisition habits. We fill this gap by directly comparing information consumption and referral patterns inside and outside of news deserts in a novel dataset of engagement with online media by millions of users on the Edge browser. We find little evidence that those in news deserts consume more low-quality sites or are more likely to be referred to low-quality sites from search engines or social media. We find some evidence that those in news deserts do consume more national news than locations with local media outlets. These results contribute to our understanding of how the loss of local newspapers has impacted online information acquisition. [ABSTRACT FROM AUTHOR]

As research into wave energy converters progresses and new developers enter the field, there arises a growing requirement for a standardized modelling approach. This article presents a novel design and dynamic emulation for a hybrid solar-wind-wave energy converter (SWWEC) which is the combination of three very well-known renewable energies: solar, wind and wave energy. Photovoltaic (PV) panels and vertical axis wind turbine (VAWT) are installed on top of the floating WEC that harness the energies from the sun and wind respectively. The SWWEC is designed with a point absorber capture system. An electrical motor is used to dynamically emulate the performance of the SWWEC under real world conditions to drive the DC generator. The present paper shows the importance and necessity of the required control schemes for the proper control of generator side converters which is present in the offshore marine substation and the most required grid connected onshore converters. The better switching signal generation for the converter control and generated harmonics elimination techniques are also presented in the paper. Outcomes of the present study are discussed and verified. [ABSTRACT FROM AUTHOR]

To tackle the challenge of low accuracy in stock prediction within high-noise environments, this paper innovatively introduces the CED-PSO-StockNet time series model. Initially, the model decomposes raw stock data using the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) technique and reconstructs the components by estimating their frequencies via the extreme point method. This process enhances component stability and mitigates noise interference. Subsequently, an Encoder-Decoder framework equipped with an attention mechanism is employed for precise prediction of the reconstructed components, facilitating more effective extraction and utilization of data features. Furthermore, this paper utilizes an Improved Particle Swarm Optimization (IPSO) algorithm to optimize the model parameters. On the Pudong Bank dataset, through ablation experiments and comparisons with baseline models, various optimization strategies incorporated into the proposed CED-PSO-StockNet model were effectively validated. Compared to the standalone LSTM model, CED-PSO-StockNet achieved a remarkable 45.59% improvement in the R2 metric. To further assess the model's generalization capability, this paper also conducted comparative experiments on the Ping An Bank dataset, and the results underscored the significant advantages of CED-PSO-StockNet in the domain of stock prediction. [ABSTRACT FROM AUTHOR]

In multiple physical fields, the mutual influence among these fields can significantly impact material elastoplasticity. This paper proposes a thermodynamic-based constitutive model that incorporates the mutual influence of multiple physical fields. Rather than treating physical field characteristics as adjustable "parameters" affecting material coefficients, the proposed model employs a thermodynamic dissipation potential derived from the Onsager reciprocity relations, accounting for thermodynamic forces coupling. This dissipation potential ensures that the thermodynamic flow in the stress field is influenced by both stress field and other physical fields thermodynamic forces, which describes the plastic flow under multiple physical fields, while preserving thermodynamic duality. The paper begins with the formulation of a generalized thermodynamic model applicable to diverse materials and types of coupled fields, which is then degraded to a specific model for AA5182-O AlMg alloy under the influence of temperature and strain rate fields coupling. Given the universal applicability of the generalized model, such degradation provides a structured approach framework for developing thermodynamics-based constitutive models. For different materials encountered in practical engineering, new thermodynamic forces can be introduced to describe their unique mechanical properties while preserving the overarching thermodynamics-based model framework, thereby facilitating model scalability. The paper concludes with a validation example, showing that within the Portevin-Le Chatelie (PLC) regime, the plastic flow stress of AA5182-O AlMg alloy decreases with increasing strain rate at low temperatures but increases at high temperatures. The accurate simulation of these distinct strain rate effects crucially relies on integrating the mutual influence of temperature field and strain rate field. [ABSTRACT FROM AUTHOR]

Based on the perspective of green technology innovation, this paper takes listed companies in China's manufacturing industry from 2012 to 2022 as the research sample, and adopts the Driscoll-Kraay standard error method to explore the relationship between intelligent manufacturing and the high-quality development of the manufacturing industry. The results show that intelligent manufacturing can promote high-quality development of manufacturing industry Green technology innovation plays an mediating role in the above relationship. The above findings still hold after considering robustness tests and endogeneity treatments. Heterogeneity analysis indicates the application of intelligent manufacturing in state-owned enterprises, CEO separately enterprises and heavily polluting industries has a stronger role in promoting the development of manufacturing industry. This paper complements the existing research results on intelligent manufacturing and also establishes a realistic path for the high-quality development of China's manufacturing industry. [ABSTRACT FROM AUTHOR]

During the oilfield development process, various factors can cause different types of reservoir damage, leading to reduced oil well production or even shutdown, and decreased water injection capacity in water wells, resulting in significant economic losses for the oilfield. However, formation damage control measures must be based on the quantitative diagnosis of the types and degrees of reservoir damage. This paper establishes a spatiotemporal evolution numerical model for 12 common types of damage during the oil and gas exploration and development process, based on the material balance theory and Fick's diffusion law in reservoir damage processes. This model achieves numerical simulation of the degree of various reservoir damage types in different spatiotemporal domains. The overall damage degree of a specific well's evolution with time and space is further simulated in simple superposition way. The sequential core flow experiment was carried out in the laboratory, and then compared with the calculation results. The accuracy is above 90%. Finally, using field test data, the simulation results show a 95% or higher degree of agreement with the actual field measurements, proving that the reservoir damage spatiotemporal evolution quantitative simulation technology established in this paper has high accuracy and practicality. [ABSTRACT FROM AUTHOR]

In federated learning, secret sharing is a key technology to maintain the privacy of participants' local models. Moreover, with the rapid development of quantum computers, existing federated learning privacy protection schemes based on secret sharing will no longer be able to guarantee the data security of participants in the post-quantum era. In addition, existing privacy protection methods have the problem of high communication and computational overhead. Although the multi-stage secret sharing scheme proposed by Pilaram et al. is one of the effective solutions to the above problems, existing studies have proven the privacy leakage risk of this scheme. This paper firstly designs a new lattice-based multi-stage secret sharing scheme Improved-Pilaram to solve the security problem, which allows participants to use public vectors to reconstruct different secret values without changing the secret sharing. Based on Improved-Pilaram, this article proposes a post-quantum secure federated learning scheme PQSF. PQSF uses double masking technology to encrypt model parameters and achieves mask reconstruction through secret sharing. Since Improved-Pilaram is multi-stage, participants do not need to update their local secret shares frequently during training. Analysis and experimental results show that the PQSF proposed in this paper reduces the communication complexity between participants and reduces the computational overhead by about 20% compared with existing solutions. [ABSTRACT FROM AUTHOR]