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Paper-based biosensors featuring immunoconjugated gold nanoparticles have gained extraordinary momentum in recent times as the platform of choice in key cases of field applications, including the so-called rapid antigen tests for SARS-CoV-2. Here, we propose a revision of this format, one that may leverage on the most recent advances in materials science and data processing. In particular, we target an amplifiable DNA rather than a protein analyte, and we replace gold nanospheres with anisotropic nanorods, which are intrinsically brighter by a factor of ~ 10, and multiplexable. By comparison with a gold-standard method for dot-blot readout with digoxigenin, we show that gold nanorods entail much faster and easier processing, at the cost of a higher limit of detection (from below 1 to 10 ppm in the case of plasmid DNA containing a target transgene, in our current setup). In addition, we test a complete workflow to acquire and process photographs of dot-blot membranes with custom-made hardware and regression tools, as a strategy to gain more analytical sensitivity and potential for quantification. A leave-one-out approach for training and validation with as few as 36 sample instances already improves the limit of detection reached by the naked eye by a factor around 2. Taken together, we conjecture that the synergistic combination of new materials and innovative tools for data processing may bring the analytical sensitivity of paper-based biosensors to approach the level of lab-grade molecular tests. [ABSTRACT FROM AUTHOR]

Paper-based biosensors featuring immunoconjugated gold nanoparticles have gained extraordinary momentum in recent times as the platform of choice in key cases of field applications, including the so-called rapid antigen tests for SARS-CoV-2. Here, we propose a revision of this format, one that may leverage on the most recent advances in materials science and data processing. In particular, we target an amplifiable DNA rather than a protein analyte, and we replace gold nanospheres with anisotropic nanorods, which are intrinsically brighter by a factor of ~ 10, and multiplexable. By comparison with a gold-standard method for dot-blot readout with digoxigenin, we show that gold nanorods entail much faster and easier processing, at the cost of a higher limit of detection (from below 1 to 10 ppm in the case of plasmid DNA containing a target transgene, in our current setup). In addition, we test a complete workflow to acquire and process photographs of dot-blot membranes with custom-made hardware and regression tools, as a strategy to gain more analytical sensitivity and potential for quantification. A leave-one-out approach for training and validation with as few as 36 sample instances already improves the limit of detection reached by the naked eye by a factor around 2. Taken together, we conjecture that the synergistic combination of new materials and innovative tools for data processing may bring the analytical sensitivity of paper-based biosensors to approach the level of lab-grade molecular tests. [ABSTRACT FROM AUTHOR]

While traditional techniques have long allowed forensic investigators to positively identify fingermarks on documents of interest, understanding the chronological sequence of events that led to their deposition is still seen as a 'holy grail' for forensic examinations. By way of example, the question of whether a mark is above or below printed text is crucial. The work herein reveals that a novel application of a recently established fingermark development technique readily allows such differentiation. The process in question allies forensic gelatin lifters with RECOVER, a development system that hinges on the polymerisation of disulfur dinitride. While the latter was specifically developed in its current form for the retrieval of prints from metal surfaces exposed to extreme conditions or washing, its ability to target surface effects allows for visualisation of surface interactions on forensic gelatin lifts. Crucially, in doing so the order in which the lifted material was originally deposited is also revealed. This, therefore, permits clear elucidation of the order of deposition of printed text and fingermarks—and does so both rapidly and in a non-invasive way. This long sought-after capability has the potential to revolutionise forensic document examinations. [ABSTRACT FROM AUTHOR]

Invasive species can be particularly disruptive when they intersect with organisms of conservation concern. Stabilizing the declining eastern migratory population of monarch butterflies (Danaus plexippus) is projected to require extensive habitat restoration across multiple land use sectors including metropolitan areas. Numerous conservation programs encourage urban citizens to plant gardens with milkweeds, the obligate larval host plants of the monarch. Here, we show that predation by Polistes dominula, an invasive paper wasp that is particularly abundant in urban settings, can turn such sites into ecological traps for monarch larvae. Polistes dominula was the predominant paper wasp seen foraging in central Kentucky pollinator gardens. In 120 observed encounters with monarch larvae on milkweeds in gardens, most second to fourth instars were killed, whereas most fifth instars escaped by thrashing or dropping. The wasps bit and carried off second instars whole, whereas third and fourth instar kills were first gutted, then processed and carried away piecemeal. Predation on sentinel larvae was much higher in urban gardens than in rural settings. The wasps exploited ornamental butterfly "hibernation boxes" in pollinator gardens as nesting habitat. Polistes dominula is an under-recognized predator that may diminish the urban sector's contributions to monarch habitat restoration. [ABSTRACT FROM AUTHOR]

Infectious diseases are among the leading causes of mortality worldwide. A new coronavirus named severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) was identified in Wuhan, China in 2019, and the World Health Organization (WHO) declared its outbreak, coronavirus disease 2019 (COVID-19), as a global pandemic in 2020. COVID-19 can spread quickly from person to person. One of the most challenging issues is to identify the infected individuals and prevent potential spread of SARS-CoV-2. Recently, anti-SARS-CoV-2 immunoglobulin M (IgM) and immunoglobulin G (IgG) antibody tests using immunochromatographic methods have been used as a complement to current detection methods and have provided information of the approximate course of COVID-19 infection. However, blood sampling causes pain and poses risks of infection at the needle puncture site. In this study, a novel patch sensor integrating porous microneedles and an immunochromatographic assay (PMNIA) was developed for the rapid detection of anti-SARS-CoV-2 IgM/IgG in dermal interstitial fluid (ISF), which is a rich source of protein biomarkers, such as antibodies. Biodegradable porous microneedles (MNs) made of polylactic acid were fabricated to extract ISF from human skin by capillary effect. The extracted ISF was vertically transported and flowed into the affixed immunoassay biosensor, where specific antibodies could be detected colorimetrically on-site. Anti-SARS-CoV-2 IgM/IgG antibodies were simultaneously detected within 3 min in vitro. Moreover, the limit of detection of anti-SARS-CoV-2 IgM and IgG concentrations was as low as 3 and 7 ng/mL, respectively. The developed device integrating porous MNs and immunochromatographic biosensors is expected to enable minimally invasive, simple, and rapid anti-SARS-CoV-2 IgM/IgG antibody testing. Furthermore, the compact size of the MN and biosensor-integrated device is advantageous for its widespread use. The proposed device has great potential for rapid screening of various infectious diseases in addition to COVID-19 as an effective complementary method with other diagnostic tests. [ABSTRACT FROM AUTHOR]

Many studies have been conducted on measuring avian influenza viruses and their hemagglutinin (HA) antigens via electrochemical principles; most of these studies have used gold electrodes on ceramic, glass, or silicon substrates, and/or labeling for signal enhancement. Herein, we present a paper-based immunosensor for label-free measurement of multiple avian influenza virus (H5N1, H7N9, and H9N2) antigens using flexible screen-printed carbon nanotube-polydimethylsiloxane electrodes. These flexible electrodes on a paper substrate can complement the physical weakness of the paper-based sensors when wetted, without affecting flexibility. The relative standard deviation of the peak currents was 1.88% when the electrodes were repeatedly bent and unfolded twenty times with deionized water provided each cycle, showing the stability of the electrodes. For the detection of HA antigens, approximately 10-μl samples (concentration: 100 pg/ml–100 ng/ml) were needed to form the antigen–antibody complexes during 20–30 min incubation, and the immune responses were measured via differential pulse voltammetry. The limits of detections were 55.7 pg/ml (0.95 pM) for H5N1 HA, 99.6 pg/ml (1.69 pM) for H7N9 HA, and 54.0 pg/ml (0.72 pM) for H9N2 HA antigens in phosphate buffered saline, and the sensors showed good selectivity and reproducibility. Such paper-based sensors are economical, flexible, robust, and easy-to-manufacture, with the ability to detect several avian influenza viruses. [ABSTRACT FROM AUTHOR]

Non-Hermitian topology is a recent hot topic in condensed matters. In this paper, we propose a novel platform drawing interdisciplinary attention: rock–paper–scissors (RPS) cycles described by the evolutionary game theory. Specifically, we demonstrate the emergence of an exceptional point and a skin effect by analyzing topological properties of their payoff matrix. Furthermore, we discover striking dynamical properties in an RPS chain: the directive propagation of the population density in the bulk and the enhancement of the population density only around the right edge. Our results open new avenues of the non-Hermitian topology and the evolutionary game theory. [ABSTRACT FROM AUTHOR]

Oily water contamination has been sighted as one of the most global environmental pollution. Herein, copper hydroxide nanorods layer was constructed onto cellulosic filter paper surface cured with polydopamine, Ag nanoparticles, and Cu NPs through immersion method. This work has been aimed to produce a superhydrophobic and superoleophilic cellulosic filter paper. The structure, crystalline, and morphological properties of these modified cellulosic filter paper were investigated. Scanning electron microscope images confirmed that the modified surface was rougher compared with the pristine surface. The contact angle measurement confirmed the hydrophobic nature of these modified surfaces with a water contact angle of 169.7°. The absorption capacity was 8.2 g/g for diesel oil and the separation efficiency was higher than 99%. It was noted that the flux in the case of low viscosity solvent as n-hexane was 9663.5 Lm−2 h−1, while for the viscous oil as diesel was 1452.7 Lm−2 h−1. [ABSTRACT FROM AUTHOR]

Zinc–air batteries proffer high energy density and cyclic stability at low costs but lack disadvantages like sluggish reactions at the cathode and the formation of by-products at the cathode. To resolve these issues, a new perovskite material, CaCu3Ti4O12 (CCTO), is proposed as an efficacious electrocatalyst for oxygen evolution/reduction reactions to develop zinc–air batteries (ZAB). Synthesis of this material adopted an effective oxalate route, which led to the purity in the electrocatalyst composition. The CCTO material is a proven potential candidate for energy applications because of its high dielectric permittivity (ε) and occupies an improved ORR-OER activity with better onset potential, current density, and stability. The Tafel value for CCTO was obtained out to be 80 mV dec−1. The CCTO perovskite was also evaluated for the zinc–air battery as an air electrode, corresponding to the high specific capacitance of 801 mAh g−1 with the greater cyclic efficiency and minimum variations in both charge/discharge processes. The highest power density (Pmax) measured was 127 mW cm−2. Also, the CCTO based paper battery shows an excellent performance achieving a specific capacity of 614 mAh g−1. The obtained results promise CCTO as a potential and cheap electrocatalyst for energy applications. [ABSTRACT FROM AUTHOR]

Polistes paper wasps are a widespread taxon inhabiting various climates. They build nests in the open without a protective outer layer, which makes them vulnerable to changing temperatures. To better understand the options they have to react to environmental variation and climate change, we here compare the thermoregulatory behavior of Polistes biglumis from cool Alpine climate with Polistes gallicus from warm Mediterranean climate. Behavioral plasticity helps both of them to withstand environmental variation. P. biglumis builds the nests oriented toward east-south-east to gain solar heat of the morning sun. This increases the brood temperature considerably above the ambience, which speeds up brood development. P. gallicus, by contrast, mostly avoids nesting sites with direct insolation, which protects their brood from heat stress on hot days. To keep the brood temperature below 40–42 °C on warm days, the adults of the two species show differential use of their common cooling behaviors. While P. biglumis prefers fanning of cool ambient air onto the nest heated by the sun and additionally cools with water drops, P. gallicus prefers cooling with water drops because fanning of warm ambient air onto a warm nest would not cool it, and restricts fanning to nests heated by the sun. [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]

Three-dimensional visualization of cellular and subcellular-structures in histological-tissues is essential for understanding the complexities of biological-phenomena, especially with regards structural and spatial relationships and pathologlical-diagnosis. Recent advancements in tissue-clearing technology, such as Magnified Analysis of Proteome (MAP), have significantly improved our ability to study biological-structures in three-dimensional space; however, their wide applicability to a variety of tissues is limited by long incubation-times and a need for advanced imaging-systems that are not readily available in most-laboratories. Here, we present optimized MAP-based method for paper-thin samples, Paper-MAP, which allow for rapid clearing and subsequent imaging of three-dimensional sections derived from various tissues using conventional confocal-microscopy. Paper-MAP successfully clear tissues within 1-day, compared to the original-MAP, without significant differences in achieved optical-transparency. As a proof-of-concept, we investigated the vasculature and neuronal-networks of a variety of human and rodent tissues processed via Paper-MAP, in both healthy and diseased contexts, including Alzheimer's disease and glioma. [ABSTRACT FROM AUTHOR]

One of the main objectives of microfluidic paper-based analytical devices is to present solutions particularly, for applications in low-resource settings. Therefore, screen-printing appears to be an attractive fabrication technique in the field, due to its overall simplicity, affordability, and high-scalability potential. Conversely, the minimum feature size attained using screen-printing is still rather low, especially compared to other fabrication methods, mainly attributed to the over-penetration of hydrophobic agents, underneath defined patterns on masks, into the fiber matrix of paper substrates. In this work, we propose the use of the over-penetration to our advantage, whereby an appropriate combination of hydrophobic agent temperature and substrate thickness, allows for the proper control of channel patterning, rendering considerably higher resolutions than prior arts. The implementation of Xuan paper and nail oil as novel substrate and hydrophobic agent, respectively, is proposed in this work. Under optimum conditions of temperature and substrate thickness, the resolution of the screen-printing method was pushed up to 97.83 ± 16.34 μm of channel width with acceptable repeatability. It was also found that a trade-off exists between achieving considerably high channel resolutions and maintaining high levels of repeatability of the process. Lastly, miniaturized microfluidic channels were successfully patterned on pH strips for colorimetric pH measurement, demonstrating its advantage on negligible sample-volume consumption in nano-liter range during chemical measurement and minimal interference on manipulation of precious samples, which for the first time, is realized on screen-printed microfluidic paper-based analytical devices. [ABSTRACT FROM AUTHOR]

Ovarian cancer has a poor cure rate and rates of relapse are high. Current recurrence detection is limited by non-specific methods such as blood testing and ultrasound. Based on reports that human epididymis four (HE4) / creatinine (CRE) ratios found in urine are elevated in ovarian cancers, we have developed a paper-based device that combines lateral flow technology and cell phone analysis to quantitatively measure HE4/CRE. Surrogate samples were used to test the performance over clinically expected HE4/CRE ratios. For HE4/CRE ratios of 2 to 47, the percent error was found to be 16.0% on average whether measured by a flatbed scanner or cell phone. There was not a significant difference between the results from the cell phone or scanner. Based on published studies, error in this method was less than the difference required to detect recurrence. This promising new tool, with further development, could be used at home or in low-resource settings to provide timely detection of ovarian cancer recurrence. [ABSTRACT FROM AUTHOR]

The study was aimed to validate paper strip sensors for the detection of pesticide residues in milk, cereal-based food, and fruit juices in comparison with GC–MS/MS under field conditions. The detection limit of pesticide using rapid paper strip sensor for organophosphate, carbamate, organochlorine, fungicide, and herbicide group ranges from 1 to 10, 1–50, 250–500, 1–50, and 1 ppb, respectively in milk and milk product, cereal-based food and fruit juices. Among 125 samples of milk samples collected from the market 33 milk samples comprising 31 raw milk and 2 pasteurized milk found positive for pesticide using the strip-based sensor. In cereal based food and fruit juice samples, 6 cereal flours and 4 fruit juices were found positive for pesticide residues. The pesticide positive samples were further evaluated quantitatively using GC–MS/MS wherein 7 samples comprised of raw milk, pasteurized milk, rice flour, wheat flour, maize flour, apple juice, and pomegranate juice have shown the presence of chlorpyrifos, chlorpyrifos-methyl, α-endosulfan, β-endosulfan DDD and DDT at trace level as well as at above MRL level. It is envisaged that the developed paper strip sensor can be a potential tool in the rapid and cost-effective screening of a large number of food samples for pesticide residues. [ABSTRACT FROM AUTHOR]

Recycled paper and some hardwood paper often display poorer mechanical properties, which hinder its practical applications and need to be addressed. In this work, cellulose nanofibrils (CNFs) obtained by a combined process of enzymatic hydrolysis and grinding (EG-CNFs), grinding and microfluidization (GH-CNFs) or TEMPO-mediated oxidation and grinding (TE-CNFs) were characterized by scanning electron microscopy (SEM) and atomic force microscopy (AFM). Moreover, CNFs were made into films on which some characterizations including X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and UV–Vis transmittance spectroscopy were implemented. Results showed that CNF fibrillation was promoted as times of passes increased in microfluidization, and CNFs pretreated by enzyme possessed shorter length. Crystallinity of CNFs was related to CNF manufacturing methods, while CNF films' transparency was correlated to CNF diameter distributions. Moreover, CNFs were applied with different dosages on recycled and hardwood paper. Lengths of CNFs, strength of CNF network, and pulp properties were critical factors affecting the mechanical strength of CNFs-enhanced paper. GH-CNFs showed better strengthened effect on tensile strength of paper than TE-CNFs and EG-CNFs. The best overall improvement was achieved at GH-CNF10 dosage of 5.0 wt% on hardwood paper. The increment of tensile index, burst index, and folding endurance were 108.32%, 104.65%, and 600%, respectively. This work aims to find out the relationship between production methods and morphologies of CNFs and how the morphological characteristics of CNFs affecting the mechanical performance of paper when they are added as strength additives. [ABSTRACT FROM AUTHOR]

The electrochemical activity of catalysts strongly depends on the uniform distribution of monodisperse Pt nanoparticles without aggregates. Here, we propose a new hydrolysis-assisted smearing method for Pt loading on a free-standing paper-type electrode. Polyacrylonitrile (PAN)-based nanofiber paper was used as the electrode, and it acted as a Pt support. Hydrolysis of the electrode tripled the number of active nucleation sites for Pt adsorption on the PAN nanofibers, thereby significantly enhancing the wettability of the nanofibers. This facilitated the uniform distribution of Pt nanoparticles without aggregate formation up to 40 wt% (about 0.8 mg/cm2) with a particle size of about 3 nm. The catalytic current of the hydrolyzed Pt electrode in CH3OH/H2SO4 solution exceeded 213 mA/cm2 Pt mg, which was considerably greater than the current was 148 mA/cm2 Pt mg for an unhydrolyzed electrode. [ABSTRACT FROM AUTHOR]

Low energy surface coatings have found wide range of applications for generating hydrophobic and superhydrophobic surfaces. Most of the studies have been related to use of a single coating material over a single substrate or using a single technique. The degree of hydrophobicity is highly dependent on fabrication processes as well as materials being coated and as such warrants a high-level study using experimental optimization leading to the evaluation of the parametric behavior of coatings and their application techniques. Also, a single platform or system which can predict the required set of parameters for generating hydrophobic surface of required nature for given substrate is of requirement. This work applies the powerful machine learning algorithms (Levenberg Marquardt using Gauss Newton and Gradient methods) to evaluate the various processes affecting the anti-wetting behavior of coated printable paper substrates with the capability to predict the most optimized method of coating and materials that may lead to a desirable surface contact angle. The major application techniques used for this study pertain to dip coating, spray coating, spin coating and inkjet printing and silane and sol–gel base coating materials. [ABSTRACT FROM AUTHOR]

Achieving an efficient catalyst in the ATRP system with a simple design, preparation from available materials, and high recyclability is a significant challenging issue. To attain the goal, herein, we used chitosan (CS)-modified cellulose filter paper (FP) as a green support for the synthesis of dip catalyst. The preparation of this catalyst involved surface treatment of the FP strips by CS coating through a dipping method, which increased the affinity of the substrate for adsorbing copper ions in the next step. The Cu@CS-FP catalyst was prepared without the requirement of any ligands. The synthesized dip-catalyst, in the form of the strips, was employed for the first time in the ATRP reaction of methyl methacrylate to assay catalytic activity. Catalytic insertion/ removal (ON/OFF) experiments were carried out during the polymerization. A reasonable control over the molecular weight with high conversion (68%) and polydispersity index of 1.32 under mild reaction conditions were obtained. Significantly, because of the facile separation of the catalyst, the amount of copper that remained in the polymer was very low (2.7 ppm). Also, the recyclability of the catalyst was investigated for five runs. The conversion in the final run was 64% without a loss of catalyst efficiency. [ABSTRACT FROM AUTHOR]

In offset printing process, poor mechanical properties and printability of paper substrate usually result in printing problems, low quality of print and waste of paper materials. Therefore, many researches focus on the quality improvement of paper substrates using suitable additives. In this work, N-methylated chitosan, including N, N-dimethyl chitosan (DMC) and N, N, N-trimethyl chitosan (TMC), were prepared and employed as coating agents to ameliorate the mechanical properties and printability of paper sheets. Analysis results showed that the mechanical strength of coated papers with DMC and TMC were largely improved, because the fibers with negative charges were prone to form electrostatic bonding with the positively charged N-methylated chitosan, thus enhancing paper strength. Particularly, compared with chitosan and DMC, the TMC-coated paper exhibited better mechanical properties, printability and surface properties due to the high cationic charge density of TMC. Therefore, surface coating with TMC is of great benefit to decrease the printing problem of paper sheets and enhance the operation speed in offset printing. This work provides a valuable reference for the amelioration of the printability and physical properties of high-quality paper products for many promising applications. [ABSTRACT FROM AUTHOR]

Cyanide-based blood poisoning can seriously damage fire victims and cause death if not detected quickly. Previous conventional methods require laboratory equipment, which are expensive and increase the duration of the analysis. Here, a simple origami based microfluidic device was introduced for point of need detection of blood cyanide concentration in people involved in fire. The device is made of four layers of paper. Each layer was in the size of 1 × 1 cm folded on each other. In this work, the blood sample was acidified by trichloroacetic acid to separate cyanide from methaemoglobin in the form of HCN gas. The produced gas released into borate buffer to recover free cyanide ions which interacted with the Pt complex ([Pt(p-MeC6H4)2(phen)]) used as a receptor in this study. Optimized conditions were applied to have a suitable interaction causing the color of the receptor to change from yellow to colorless. The color changes were recorded by a smartphone, and the sensor response was calculated by the routine image analysis software. The assay was capable of determining cyanide ions at different concentrations in the range of 1.0 to 100.0 µmol L−1. The detection limit of these determination was equal to 0.4 µmol L−1. The assay responses were not affected by the interfering species. As a practical analysis, the proposed sensor was applied to determine cyanide ions in the blood sample of 20 studied fire survivors and 10 controls with high accuracy. [ABSTRACT FROM AUTHOR]

Paper spray ionization (PSI) mass spectrometry (MS) is an emerging tool for ambient reaction monitoring via microdroplet reaction acceleration. PSI-MS was used to accelerate and monitor the time course of the reaction of dansyl chloride with aniline, in acetonitrile, to produce dansyl aniline. Three distinct PSI arrangements were explored in this study representing alternative approaches for sample loading and interaction; conventional single tip as well as two novel setups, a dual-tip and a co-axial arrangement were designed so as to limit any on-paper interaction between reagents. The effect on product abundance was investigated using these different paper configurations as it relates to the time course and distance of microdroplet travel. It was observed that product yield increases at a given distance and then decreases thereafter for all PSI configurations. The fluorescent property of the product (dansyl aniline) was used to visually inspect the reaction progress on the paper substrate during the spraying process. Amongst the variety of sample loading methods the novel dual-tip arrangement showed an increased product yield and microdroplet density, whilst avoiding any on-paper interaction between the reagents. [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]

We developed a disposable paper battery aiming to reduce the environmental impact of single-use electronics for applications such as point of care diagnosis, smart packaging and environmental sensing. The battery uses Zinc as a biodegradable metal anode, graphite as a nontoxic cathode material and paper as a biodegradable substrate. To facilitate additive manufacturing, we developed electrodes and current collector inks that can be stencil printed on paper to create water-activated batteries of arbitrary shape and size. The battery remains inactive until water is provided and absorbed by the paper substrate, taking advantage of its natural wicking behavior. Once activated, a single cell provides an open circuit potential of 1.2 V and a peak power density of 150 µW/cm2 at 0.5 mA. As a proof of concept, we fabricated a two cell battery and used it to power an alarm clock and its liquid crystal display. [ABSTRACT FROM AUTHOR]

Graphite pencil stroked electrodes for paper-based Microfluidic devices are gaining immense attention due to their electrochemical properties, cost efficiency, and ease-of-use. However, their widespread use has been hindered by the challenges associated with their manual fabrication such as non-uniformity in graphite deposition, applied pressure, etc. This work presents the design and development of an automated graphite pencil stroking device for graphite electrode fabrication with high efficiency through a compact, inexpensive and automatic process, with reduced fabrication time and human intervention leading to more uniformity. The motion platform of Graphtec plotter was used to create multiple strokes with the help of the proposed device. Such inexpensive graphite electrodes (less than the US $1) have been observed to be porous in nature, acting as diffusion agents. The automated graphite electrodes were used to study the performance of microfluidic paper fuel cells (MPFCs) with formic acid, oxygen, and sulphuric acid acting as fuel, oxidising agent and electrolyte respectively. From this configuration, the maximum current density and power density were measured to be 1,305.5 µA cm−2 and 135.5 µW cm−2, respectively at 0.3 V stable OCP at 100 strokes. Overall, the study enumerates the development of an automated pencil stroke device for fabricating graphite electrodes, which can potentially be harnessed in numerous miniaturized paper based applications. [ABSTRACT FROM AUTHOR]

Development of paper-based microfluidic devices that perform colorimetric measurements requires quantitative image analysis. Because the design geometries of paper-based microfluidic devices are not standardized, conventional methods for performing batch measurements of regularly spaced areas of signal intensity, such as those for well plates, cannot be used to quantify signal from most of these devices. To streamline the device development process, we have developed an open-source program called ColorScan that can automatically recognize and measure signal-containing zones from images of devices, regardless of output zone geometry or spatial arrangement. This program, which measures color intensity with the same accuracy as standard manual approaches, can rapidly process scanned device images, simultaneously measure identified output zones, and effectively manage measurement results to eliminate requirements for time-consuming and user-dependent image processing procedures. [ABSTRACT FROM AUTHOR]

Analyzing electrolytes in urine, such as sodium, potassium, calcium, chloride, and nitrite, has significant diagnostic value in detecting various conditions, such as kidney disorder, urinary stone disease, urinary tract infection, and cystic fibrosis. Ideally, by regularly monitoring these ions with the convenience of dipsticks and portable tools, such as cellphones, informed decision making is possible to control the consumption of these ions. Here, we report a paper-based sensor for measuring the concentration of sodium, potassium, calcium, chloride, and nitrite in urine, accurately quantified using a smartphone-enabled platform. By testing the device with both Tris buffer and artificial urine containing a wide range of electrolyte concentrations, we demonstrate that the proposed device can be used for detecting potassium, calcium, chloride, and nitrite within the whole physiological range of concentrations, and for binary quantification of sodium concentration. [ABSTRACT FROM AUTHOR]

A novel strategy for the direct analysis of non-conjugated steroids in water using paper spray mass spectrometry (PS-MS) has been developed. PS-MS was used in the identification and quantification of non-conjugated (free) steroids in fish tank water samples. Data shown herein indicates that individual amounts of free steroids can be detected in aqua as low as; 0.17 ng/µL, 0.039 ng/µL, 0.43 ng/µL, 0.0076 ng/µL for aldosterone, corticosterone, cortisol, and β-estrone, respectively, and with an average relative standard deviation of ca. < 10% in the positive ion mode using PS-MS/MS. Direct detection of free steroids in a raw water mixture, from aquaculture, without prior sample preparation is demonstrated. The presence of free steroids released in fish water samples was confirmed via tandem mass spectrometry using collision-induced dissociation. This approach shows promise for rapid and direct water quality monitoring to provide a holistic assessment of non-conjugated steroids in aqua. [ABSTRACT FROM AUTHOR]

Triboelectric nanogenerators (TENGs) offer an emerging market of self-sufficient power sources, converting the mechanical energy of the environment to electricity. Recently reported high power densities for the TENGs provide new applications opportunities, such as self-powered sensors. Here in this research, a flexible graphene oxide (GO) paper was fabricated through a straightforward method and utilized as the electrode of TENGs. Outstanding power density as high as 1.3 W.m−2, an open-circuit voltage up to 870 V, and a current density of 1.4 µA.cm−2 has been extracted in vertical contact-separation mode. The all-flexible TENG has been employed as a self-powered humidity sensor to investigate the effect of raising humidity on the output voltage and current by applying mechanical agitation in two forms of using a tapping device and finger tapping. Due to the presence of superficial functional groups on the GO paper, water molecules are inclined to be adsorbed, resulting in a considerable reduction in both generated voltage (from 144 V to 14 V) and current (from 23 µA to 3.7 µA) within the range of relative humidity of 20% to 99%. These results provide a promising applicability of the first suggested sensitive self-powered GO TENG humidity sensor in portable/wearable electronics. [ABSTRACT FROM AUTHOR]

The gut microbiota is recognized as having major impact in health and disease. Sample storage is an important aspect to obtain reliable results. Mostly recommended is immediate freezing, however, this is not always feasible. Faecal occult blood test (FOBT) papers are an appealing solution in such situations, and most studies find these to be applicable, showing no major changes within 7 days storage at room temperature (RT). As fieldwork often requires RT storage for longer periods, evaluation of this is warranted. We performed 16S rRNA gene sequencing of 19 paired faecal samples immediately frozen or kept five weeks and five months at RT on FOBT papers. Alpha-diversity evaluation revealed no effect of FOBT storage, and evaluation of beta-diversity showed that host explained 65% of community variation, while storage method explained 5%. Evaluation of community dispersion and the Firmicutes/Bacteroidetes ratio revealed a larger effect of storage time for fresh-frozen samples. Single taxa evaluation (order-to-genus level) showed significant alterations of four (of 37) genera after five weeks and five genera after five months. When comparing the two timepoints, alterations were only detectable for fresh-frozen samples. Our findings reveal that long term storage on FOBT papers is an applicable approach for microbiota research. [ABSTRACT FROM AUTHOR]

Rapid urbanization has resulted in the substantial population growth in metropolitan areas. However, existing research on population change of the cities predominantly draws on grid statistical data at the administrative level, overlooking the intra-urban variegation of population change. Particularly, there is a lack of attention given to the spatio-temporal change of population across different urban forms and functions. This paper therefore fills in the lacuna by clarifying the spatio-temporal characteristics of population growth in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) from 2000 to 2020 through the methods of local climate zone (LCZ) scheme and urban–rural gradients. The results showed that: (1) High population density was observed in the compact high-rise (LCZ 1) areas, with a noticeable decline along urban–rural gradients. (2) The city centers of GBA experienced the most significant population growth, while certain urban fringes and rural areas witnessed significant population shrinkage. (3) The rate of growth tended to slow down after 2010, but the uneven development of population-based urbanization was also noticeable, as urbanization and industrialization varied across different LCZ types and cities in GBA. This paper therefore contributes to a deeper understanding of population change and urbanization by clarifying their spatio-temporal contingences at landscape level. [ABSTRACT FROM AUTHOR]

In modern tunnel construction, TBM (Tunnel Boring Machine) plays a very important role. In response to the needs of tunnel wall reinforcement and TBM automated construction for tunnel construction, a shotcrete mechanism mounted on the TBM is designed. In order to evaluate the kinematic performance of the mechanism, this paper studies the forward and inverse kinematics and spatial architecture of the TBM shotcrete robot. Firstly, based on the D–H parameter method, the number of joints and links is determined and structural analysis is performed to obtain the robot's forward kinematics equation, achieving the mapping between joint space and pose space. Then, by determining the joint variables, the mapping of the end tool in Cartesian space is achieved. Finally, based on the Monte Carlo random sampling method, the workspace of the robot is constructed, and its reachability and flexibility within the robot workspace are evaluated. The performance of the device is verified by building a prototype, which meets the requirements well. Through the research in this paper, it can provide theoretical basis and guidance for the design and control of the shotcrete robot. [ABSTRACT FROM AUTHOR]

The traditional diagnostic process for autism spectrum disorder (ASD) is subjective, where early and accurate diagnosis significantly affects treatment outcomes and life quality. Thus, improving ASD diagnostic methods is critical. This paper proposes ASD-SWNet, a new shared-weight feature extraction and classification network. It resolves the issue found in previous studies of inefficiently integrating unsupervised and supervised learning, thereby enhancing diagnostic precision. The approach utilizes functional magnetic resonance imaging to improve diagnostic accuracy, featuring an autoencoder (AE) with Gaussian noise for robust feature extraction and a tailored convolutional neural network (CNN) for classification. The shared-weight mechanism utilizes features learned by the AE to initialize the convolutional layer weights of the CNN, thereby integrating AE and CNN for joint training. A novel data augmentation strategy for time-series medical data is also introduced, tackling the problem of small sample sizes. Tested on the ABIDE-I dataset through nested ten-fold cross-validation, the method achieved an accuracy of 76.52% and an AUC of 0.81. This approach surpasses existing methods, showing significant enhancements in diagnostic accuracy and robustness. The contribution of this paper lies not only in proposing new methods for ASD diagnosis but also in offering new approaches for other neurological brain diseases. [ABSTRACT FROM AUTHOR]

Low-emissions livestock production can be achieved through scaling production systems integrating trees, forages, and livestock within the same area. Such systems are known as silvopastoral production systems (SPS). However, despite SPS reported benefits, adoption rates globally remain low. This paper, therefore, aims to inform land use policy oriented towards increasing SPS adoption. This study intends to capture this by assessing SPS adoption benefits, identifying determinants of SPS adoption, and thus to contribute to policy for scaling low-emissions livestock production. Data was collected on socioeconomic status, livestock farming technical and economic indicators, and farm and paddock practices through farm-level surveys in four municipalities in the Amazon Piedmont of Colombia. Unlike previous studies that assume homogeneous farm management, when in fact, it is heterogeneous, this study assessed SPS adoption determinants using the paddock (n = 2819) as the unit of analysis. This methodological approach is consistent with paddock-level land use decisions taken by farmers based on socioeconomic and biophysical factors such as soil financial resources, type, and topography. The methodological approach allows us to provide new insights into the determinant of adopting SPS and an understanding of intra-farm level land use decisions. The results show that the adoption of SPS at both paddocks and farm levels in Caquetá is low. The main factors associated with higher SPS adoption levels at the paddock level are framed in gender, resources, and knowledge. We observe that women are more motivated to conserve the environment. Cattle paddocks managed by women, smaller in size, and those with more SPS-related projects show a tendency for medium or high SPS adoption. Furthermore, the positive relationship between access to credit and SPS adoption emphasizes the importance of financial resources tailored to SPS projects. Enhancing gender roles, improving access to finance in land use, and providing training programs on SPS systems can contribute to low-emission livestock production in Colombia. This research paper highlights the significance of implementing diverse management strategies and reaching out to farmers not involved in SPS projects. It emphasizes investments in low-emission livestock production, especially for female heads of households. This approach recognizes the broader benefits of SPS, beyond production and financial gains, promoting the division of paddocks and the adoption of SPS. [ABSTRACT FROM AUTHOR]

In the past two decades, Europe has witnessed a significant transition in the design codes used for assessing foundation structures, with the widespread adoption of the Eurocodes (EC). This shift remains a pertinent topic within the engineering community, particularly concerning the transition from traditional design methodologies to those prescribed by the Eurocodes, as well as the potential for fully probabilistic design. While the Eurocodes’ methodology is described as probabilistic, it is crucial to recognize that the achievement of the target reliability level is predominantly facilitated through a system of partial safety factors. These factors are integrated into the calculation algorithm as fixed values, rendering the process essentially deterministic. To refine these calculations for more accurate reliability estimates—expressed in terms of failure probability—a genuinely probabilistic framework is required, termed as fully probabilistic computation. This paper aims to elucidate the fully probabilistic calculation approach for the broader professional community, using the geotechnical application of shallow foundations as an illustrative example. We present a comparative analysis of this advanced approach with the standard foundation design according to EC7 and ČSN 731001, the latter being a precursor in Europe for implementing the partial safety factor method. The discussion extends to a practical demonstration of full probabilistic design juxtaposed against the conventional partial safety factor method, using a shallow foundation case study. Furthermore, the paper delves into the impact of the tail behavior of uncertain or spatially varying soil parameters on the theoretical probability of failure, underscoring its significance in foundation design. [ABSTRACT FROM AUTHOR]

Advances in computer image recognition have significantly impacted many industries, including healthcare, security and autonomous systems. This paper aims to explore the potential of improving image algorithms to enhance computer image recognition. Specifically, we will focus on regression methods as a means to improve the accuracy and efficiency of identifying images. In this study, we will analyze various regression techniques and their applications in computer image recognition, as well as the resulting performance improvements through detailed examples and data analysis. This paper deals with the problems related to visual image processing in outdoor unstructured environment. Finally, the heterogeneous patterns are converted into the same pattern, and the heterogeneous patterns are extracted from the fusion features of data modes. The simulation results show that the perception ability and recognition ability of outdoor image recognition in complex environment are improved. [ABSTRACT FROM AUTHOR]

The Friendship Paradox is a simple and powerful statement about node degrees in a graph. However, it only applies to undirected graphs with no edge weights, and the only node characteristic it concerns is degree. Since many social networks are more complex than that, it is useful to generalize this phenomenon, if possible, and a number of papers have proposed different generalizations. Here, we unify these generalizations in a common framework, retaining the focus on undirected graphs and allowing for weighted edges and for numeric node attributes other than degree to be considered, since this extension allows for a clean characterization and links to the original concepts most naturally. While the original Friendship Paradox and the Weighted Friendship Paradox hold for all graphs, considering non-degree attributes actually makes the extensions fail around 50% of the time, given random attribute assignment. We provide simple correlation-based rules to see whether an attribute-based version of the paradox holds. In addition to theory, our simulation and data results show how all the concepts can be applied to synthetic and real networks. Where applicable, we draw connections to prior work to make this an accessible and comprehensive paper that lets one understand the math behind the Friendship Paradox and its basic extensions. [ABSTRACT FROM AUTHOR]

To reveal complex causes of aircraft events, this paper aims to mine association rules between the trigger probability and relative strength via a modified Apriori algorithm. Clustering is adopted for data preprocessing and TF–IDF value calculation. Causative item sets of aircraft events are obtained based on the accident causation 2–4 model and are coded to establish code indicators. By avoiding the use of statistical methodologies to resolve not-a-number (NaN) values for altering the interrelations among causes, an enhancement in the Apriori algorithm is proposed by considering frequent items. By extracting frequent patterns, in this paper, all the association rules that satisfy three perspectives (support, confidence and lift) are determined by constantly generating and pruning candidate item sets. A network graph is used to visualize the association rules between different unsafe events and all types of causes. Finally, 9835 representative pieces of data, including general unsafe events, general incidents and serious incidents from the Southwest Air Traffic Management Bureau, are selected for analysis. The results show that improper energy allocation, poor conflict resolution ability, inadequate onsite management duties, adoption of a luck mentality, and occurrence of controller oversight are highly correlated with general unsafe events, and failure to rectify incorrect recitation is notably correlated with general incidents, while inadequate manual promotion, lack of conflict judgement and insufficient safety management are strongly correlated with serious incidents. This study quantitatively reveals the potential patterns and characteristics of mutual interactions among various types of historical aircraft events and highlights directions for controllable prevention and prediction of aircraft events. [ABSTRACT FROM AUTHOR]

As a facilitator of smart upgrading, digital twin (DT) is emerging as a driving force in prognostics and health management (PHM). Faults can lead to degradation or malfunction of industrial assets. Accordingly, DT-driven PHM studies are conducted to improve reliability and reduce maintenance costs of industrial assets. However, there is a lack of systematic research to analyze and summarize current DT-driven PHM applications and methodologies for industrial assets. Therefore, this paper first analyzes the application of DT in PHM from the application field, aspect, and hierarchy at application layer. The paper next deepens into the core and mechanism of DT in PHM at theory layer. Then enabling technologies and tools for DT modeling and DT system are investigated and summarized at implementation layer. Finally, observations and future research suggestions are presented. [ABSTRACT FROM AUTHOR]

In practical engineering, the development of surface cracks is one of the most important reasons for the destruction of the rock mass, and the development of complex morphology fractures on the rock mass surface significantly influences rock mass mechanics. This paper addresses the freeze–thaw damage issue in rock mass containing surface fractures in cold regions. Tuffs and a control group are selected as research samples, with the control group being prefabricated surface jointed specimens with an inclination angle of 70° and a fracture depth ratio d (crack depth) /t (sample width) of 0.26. The study analyzes the mass, wave velocity loss, macro-microcosmic fracture damage morphology, and mechanical properties of the two specimen groups through laboratory freeze–thaw cycle tests, uniaxial compression tests, and scanning electron microscopy examinations. The results show an overall decrease in mass, wave velocity, and uniaxial compressive strength as the cycle number increases, with the prefabricated jointed group samples showing more significant changes. However, the two specimen groups exhibit different macroscopic failure fracture states. In addition, scanning electron microscopy images illustrate that after freeze–thaw cycles, the large rock mass particles break into smaller fragments, resulting in looser particle arrangements and a transition from initial surface cementation to point contact., which weakens the compressive strength of the rock mass. The paper also explains the mechanism of the diminishing impact of freeze–thaw cycles on the strength of the rock mass after a certain number of cycles. The research outcomes hold significant reference value for engineering construction in cold regions. [ABSTRACT FROM AUTHOR]

Quantum computing has already demonstrated great computational potential across multiple domains and has received more and more attention. However, due to the connectivity limitations of Noisy Intermediate-Scale Quantum (NISQ) devices, most of the quantum algorithms cannot be directly executed without the help of inserting SWAP gates. Nevertheless, more SWAP gates lead to a longer execution time and, inevitably, lower fidelity of the algorithm. To this end, this paper proposes an optimized qubit mapping algorithm based on a dynamic look-ahead strategy to minimize the number of SWAP gates inserted. Firstly, a heuristic algorithm is proposed based on maximizing physical qubit connectivity to generate the optimal initial qubit mapping, which reduces the need for logical qubit shifts during subsequent SWAP gate insertion. Secondly, in the form of directed acyclic graphs, we identify quantum gates that violate the constraints of physical coupling and insert SWAP gates to remap qubits, thereby overcoming the limitations of qubit interactions. Finally, the optimal SWAP gate insertion strategy is built by comparing the cost of different SWAP gate insertion strategies through a multi-window look-ahead strategy to reduce the number of SWAP gates inserted. The experimental results show that the strategy in this paper decreases the number of SWAP gate insertions and significantly reduces the depth of quantum circuits when performing qubit mapping compared with state-of-the-art methods. [ABSTRACT FROM AUTHOR]

A Virtual Power Plant (VPP) is a centralized energy system that manages, and coordinates distributed energy resources, integrating them into a unified entity. While the physical assets may be dispersed across various locations, the VPP integrates them into a virtual unified entity capable of responding to grid demands and market signals. This paper presents a tri-level hierarchical coordinated operational framework of VPP. Firstly, an Improved Pelican Optimization Algorithm (IPOA) is introduced to optimally schedule Distributed Energy Resources (DERs) within the VPP, resulting in a significant reduction in generation costs. Comparative analysis against conventional algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) demonstrates IPOA's superior performance, achieving an average reduction of 8.5% in generation costs across various case studies. The second stage focuses on securing the optimized generation data from rising cyber threats, employing the capabilities of machine learning, preferably, a convolutional autoencoder to learn the normal patterns of the optimized data to detect deviations from the optimized generation data to prevent suboptimal decisions. The model exhibits exceptional performance in detecting manipulated data, with a False Positive Rate (FPR) of 1.92% and a Detection Accuracy (DA) of 98.06%, outperforming traditional detection techniques. Lastly, the paper delves into the dynamic nature of the day ahead market that the VPP participates in. In responding to the grid by selling its optimized generated power via the day-ahead market, the VPP employs the Prophet model, another machine learning technique to forecast the spot market price for the day-ahead to mitigate the adverse effects of price volatility. By utilizing Prophet forecasts, the VPP achieves an average revenue increase of 15.3% compared to scenarios without price prediction, emphasizing the critical role of predictive analytics in optimizing economic gains. This tri-level coordinated approach adopted addresses key challenges in the energy sector, facilitating progress towards achieving universal access to clean and affordable energy. [ABSTRACT FROM AUTHOR]

Knowledge diffusion in regional innovation ecosystems is an important factor that influences the regional innovation efficiency. In regional innovation ecosystems under digital empowerment, the knowledge diffusion enables the optimal allocation of innovation resources and promotes the sustainable development and ecological evolution of regional innovation ecosystems. In this paper, a SEIR (Susceptible–Exposed–Infected–Recovered) model is proposed for knowledge diffusion in regional innovation ecosystems under digitization. The basic reproduction number of the proposed model is calculated and its stability is validated. Finally, the expressions for the optimal control system and the optimal control parameters are presented. According to the research conclusions of this paper, the knowledge-diffusion ability of innovation agents in an innovation ecosystem affects the knowledge diffusion in a system; the contact rate between innovation agents affects the efficiency of knowledge diffusion in the system and the structure of the system; the digital transmission ability of innovation agents affects the breadth of knowledge diffusion in the system; and the self-learning ability of innovation agents affects the efficiency of knowledge diffusion in the system.The digital technologies help heterogeneous innovation agents in regional innovation ecosystems to break down the knowledge silos. At the same time, the digital technologies enhance the ability of innovation agents to absorb and learn knowledge in regional innovation ecosystems under digitization, thereby increasing the infection rate of knowledge diffusion in such systems.These conclusions extend the theoretical boundaries of innovation ecosystems and knowledge diffusion and offer management implications for enterprises and governments in decision-making. [ABSTRACT FROM AUTHOR]

To deal with the highly nonlinear and time-varying characteristics of Batch Process, a model named adaptive stacking approximate kernel based broad learning system is proposed in this paper. This model innovatively introduces the approximate kernel based broad learning system (AKBLS) algorithm and the Adaptive Stacking framework, giving it strong nonlinear fitting ability, excellent generalization ability, and adaptive ability. The Broad Learning System (BLS) is known for its shorter training time for effective nonlinear processing, but the uncertainty brought by its double random mapping results in poor resistance to noisy data and unpredictable impact on performance. To address this issue, this paper proposes an AKBLS algorithm that reduces uncertainty, eliminates redundant features, and improves prediction accuracy by projecting feature nodes into the kernel space. It also significantly reduces the computation time of the kernel matrix by searching for approximate kernels to enhance its ability in industrial online applications. Extensive comparative experiments on various public datasets of different sizes validate this. The Adaptive Stacking framework utilizes the Stacking ensemble learning method, which integrates predictions from multiple AKBLS models using a meta-learner to improve generalization. Additionally, by employing the moving window method—where a fixed-length window slides through the database over time—the model gains adaptive ability, allowing it to better respond to gradual changes in industrial Batch Process. Experiments on a substantial dataset of penicillin simulations demonstrate that the proposed model significantly improves predictive accuracy compared to other common algorithms. [ABSTRACT FROM AUTHOR]

Deep-buried tunnels with weak surrounding rock are frequently encountered issues in traffic engineering. It plays an important role in the excavation process and the project operation. This paper applies the theoretical analysis and laboratory test related to four different conditions in terms of their thickness to determine the mechanical response of deep-buried tunnel lining. Then, the energy dissipative structure theory is employed to explain the experimental results. This paper has made the following achievements: firstly, it is found that the toughness of the secondary lining was found to be often the most important indicator of tunnel safety, with better-toughness linings having higher tensile strength and crack resistance. Secondly, it suggests that the inclusion of steel reinforcement in the concrete lining can effectively improve the secondary lining toughness. Finally, it proves that the more ductile liner had more energy, higher load-carrying capacity, and was better able to maintain the overall stability of the structure. [ABSTRACT FROM AUTHOR]

Online rumors are widespread and difficult to identify, which bring serious harm to society and individuals. To effectively detect and govern online rumors, it is necessary to conduct in-depth semantic analysis and understand the content features of rumors. This paper proposes a TFI domain ontology construction method, which aims to achieve semantic parsing and reasoning of the rumor text content. This paper starts from the term layer, the frame layer, and the instance layer, and based on the reuse of the top-level ontology, the extraction of core literature content features, and the discovery of new concepts in the real corpus, obtains the core classes (five parent classes and 88 subclasses) of the rumor domain ontology and defines their concept hierarchy. Object properties and data properties are designed to describe relationships between entities or their features, and the instance layer is created according to the real rumor datasets. OWL language is used to encode the ontology, Protégé is used to visualize it, and SWRL rules and pellet reasoner are used to mine and verify implicit knowledge of the ontology, and judge the category of rumor text. This paper constructs a rumor domain ontology with high consistency and reliability. [ABSTRACT FROM AUTHOR]

The structural plane characteristic was the most critical factor for determining the self-stability ability of deep foundation pit vertical-rock-wall in layered rock stratum. Multiple methods such as model testing, numerical calculation, and theoretical calculation were utilized comprehensively in this paper. The self-stabilizing control effect on the deep foundation pits vertical-rock-wall that under the different structural plane inclination angle (α) and under the different structural plane strength was systematically studied. The results indicated that the overall variation trend of "Sharp decrease ~ Slow decrease ~ Slow increase ~ Sharp increase" in the symmetrical distribution for the self-stability critical height (Hcr) varied with the gradually increasing of α was presented. Meanwhile, the variation trend of "continuously decreasing and rapidly decreasing first, and then slowly decreasing and tending to stabilize" with the structural plane strength reduction coefficient (k). The key factor to control the self-stability of the deep foundation pit vertical-rock-walls lied in fully grasping and utilizing the basic characteristics of rock structural planes. The research results of this paper provided the theoretical basis for scientifically determining the safety level and designing reasonable support structures of the deep foundation pit vertical-rock-walls in layered rock stratum. [ABSTRACT FROM AUTHOR]

Perovskite solar cells (PSCs) have gained much attention in recent years because of their improved energy conversion efficiency, simple fabrication process, low processing temperature, flexibility, light weight, and low cost of constituent materials when compared with their counterpart silicon based solar cells. Besides, stability and toxicity of PSCs and low power conversion efficiency have been an obstacle towards commercialization of PSCs which has attracted intense research attention. In this research paper, a Glass/Cu2O/CH3NH3SnI3/ZnO/Al inverted device structure which is made of cheap inorganic materials, n-type transparent conducting oxide (TCO)-free, stable, photoexcited toxic-free perovskite have been carefully designed, simulated and optimized using a one-dimensional solar cell capacitance simulator (SCAPS-1D) software. The effects of layers' thickness, perovskite's doping concentration and back contact electrodes have been investigated, and the optimized structure produced an open circuit voltage (Voc) of 1.0867 V, short circuit current density (JSC) of 33.4942 mA/cm2, fill factor (FF) of 82.88% and power conversion efficiency (PCE) of 30.17%. This paper presents a model that is first of its kind where the highest PCE performance and eco-friendly n-type TCO-free inverted CH3NH3SnI3 based perovskite solar cell is achieved using all-inorganic transport materials. [ABSTRACT FROM AUTHOR]

Reservoir flood control scheduling is a challenging optimization task, particularly due to the complexity of various constraints. This paper proposes an innovative algorithm design approach to address this challenge. Combining the basic walrus optimization algorithm with the adaptive ε-constraint method and introducing the SPM chaotic mapping for population initialization, spiral search strategy, and local enhancement search strategy based on Cauchy mutation and reverse learning significantly enhances the algorithm's optimization performance. On this basis, innovate an adaptive approach ε A New Algorithm for Constraints and Multi Strategy Optimization Improvement (ε-IWOA). To validate the performance of the ε-IWOA algorithm, 24 constrained optimization test functions are used to test its optimization capabilities and effectiveness in solving constrained optimization problems. Experimental results demonstrate that the ε-IWOA algorithm exhibits excellent optimization ability and stable performance. Taking the Taolinkou Reservoir, Daheiting Reservoir, and Panjiakou Reservoir in the middle and lower reaches of the Luanhe River Basin as a case study, this paper applies the ε-IWOA algorithm to practical reservoir scheduling problems by constructing a three-reservoir flood control scheduling system with Luanxian as the control point. A comparative analysis is conducted with the ε-WOA, ε-DE and ε-PSO (particle swarm optimization) algorithms.The experimental results indicate that ε-IWOA algorithm performs the best in optimization, with the occupied flood control capacity of the three reservoirs reaching 89.32%, 90.02%, and 80.95%, respectively. The control points in Luan County can reduce the peak by 49%.This provides a practical and effective solution method for reservoir optimization scheduling models. This study offers new ideas and solutions for flood control optimization scheduling of reservoir groups, contributing to the optimization and development of reservoir scheduling work. [ABSTRACT FROM AUTHOR]

With the rapid development of modern medical technology and the dramatic increase in the amount of medical data, traditional centralized medical information management is facing many challenges. In recent years blockchain, which is a peer-to-peer distributed database, has been increasingly accepted and adopted by different industries and use cases. Key areas of healthcare blockchain applications include electronic medical record (EMR) management, medical device supply chain management, remote condition monitoring, insurance claims and personal health data (PHD) management, among others. Even so, there are a number of challenges in applying blockchain concepts to healthcare and its data, including interoperability, data security privacy, scalability, TPS and so on. While these challenges may hinder the development of blockchain in healthcare scenarios, they can be improved with existing technologies In this paper, we propose a blockchain-based healthcare operations management framework that is combined with the Interplanetary File System (IPFS) for managing EMRs, protects data privacy through a distributed approach while ensuring that this medical ledger is tamper-proof. Doctors act as full nodes, patients can participate in network maintenance either as light nodes or as full nodes, and the hospital acts as the endpoint database of data, i.e., the IPFS node, which saves the arithmetic power of nodes and allows the data stored in the hospitals and departments to be shared with the other organizations that have uploaded the data. Therefore, the integration of blockchain and zero-knowledge proof proposed in this paper helps to protect data privacy and is efficient, better scalable, and more throughput. [ABSTRACT FROM AUTHOR]