MoS2 has long been considered as a promising catalyst for hydrogen production. At present, there are many strategies to further improve its catalytic performance, such as edge engineering, defect engineering, phase engineering and so on. However, at present, there is still a great deal of controversy about the mechanism of MoS2 catalytic hydrogen production. For example, it is generally believed that the base plane of MoS2 is inert, but it has been reported that the inert base plane can undergo a transient phase transition in the catalytic process to play the catalytic role, which is contrary to the common understanding that the catalytic activity is only at the edge. Therefore, it is necessary to further understand the mechanism of MoS2 catalytic hydrogen production. In this article, we summarized the latest research progress on the catalytic hydrogen production of MoS2, which is of great significance for revisited the mechanism of MoS2 catalytic hydrogen production.

Retention mechanisms in HILIC have been investigated and reported in literature. However, the current understanding of the retention mechanisms is qualitative and lacks quantitative details. Previously, mechanism elucidation was based on indirect evidence, and unambiguous assignment of retention mechanisms has not been reported based on direct data. This study aims to quantitatively determine the contributions of two major retention mechanisms in HILIC, hydrophilic partitioning and surface adsorption to the overall retention of neutral compounds. Using the methodologies we developed previously, the phase ratio for adsorbed water layer and distribution coefficients were measured and used to calculate the retention factors attributed to hydrophilic partitioning. The methodology allows the determination of the contribution of surface adsorption simultaneously. The evaluation of five test compounds demonstrates that the retention may be controlled by hydrophilic partitioning, surface adsorption or both depending on compound characteristics. Quantitative assessment of retention mechanisms also makes it possible to better understand the effect of acetonitrile on retention in HILIC.

Extracellular vesicles (EVs) are emerging mediators of intracellular and inter-organ communications in cardiovascular diseases (CVDs), especially in the pathogenesis of heart failure through the transference of EV-containing bioactive substances. microRNAs (miRNAs) are contained in EV cargo and are involved in the progression of heart failure. Over the past several years, a growing body of evidence has suggested that the biogenesis of miRNAs and EVs are tightly regulated, and the sorting of miRNAs into EVs is highly selective and tightly controlled. Extracellular miRNAs, in particular circulating EV-miRNAs, have shown promising potential as prognostic and diagnostic biomarkers for heart failure and as therapeutic targets. In this review, we summarize the latest progress concerning the role of EV-miRNAs in HF and their application in a therapeutic strategy development for heart failure.

Highly efficient, broadband and distinctively structured electromagnetic wave (EMW) absorption materials exhibit huge exceptions with multi-functions in both military and civilian fields. Searching the relationship between structural and EMW performance is beneficial to develop outstanding microwave absorption materials, and has become an attractive research topic. In this study, we briefly reviewed the different EMW absorption mechanisms and key influence factors, then, present the latest developments in low-dimensional (LD) EMW absorption materials. We provide a comprehensive discussion of remarkable examples and summarize the main information related to the structure-function relationship of dimensional design and structural engineering in order to facilitate the rapid evolution of this fascinating field.

With the evolution of toxic chemicals continuing to progress, developing methods for the destruction of chemical warfare agents (CWAs) has become an increasingly important research topic. Metal-organic frameworks (MOFs) are a class of porous crystalline solids that have sparked interest in this area. Due to their exceptional porosities and large surface areas, MOFs possess superior adsorption, reactivity, and catalytic abilities, making them structurally ideal candidates for the capture and decomposition of target species. Additionally, the tunable networks of MOFs allow their chemical functionalities to be customized for various applications and operating conditions, making them practicable in personal protective equipment and adjustable to dynamic environments. This paper reviews experimental and computational studies on CWA removal by MOFs, with a special emphasis on nerve agent (GB, GD, and VX) removal via hydrolysis and sulfur mustard (HD) removal via selective photooxidation. With extraordinary structural stability and reusability, zirconium-based MOFs are the most promising materials for hydrolytic and photooxidative degradation of CWAs and are thus the primary focus of this work. First-principles approximations of the intrinsic catalytic reaction mechanisms towards different agents in Zr-MOFs are summarized, and developments in the structure-property relationships governing Zr-MOF design rules for efficient degradation in the aqueous and solid phases are discussed. We also examine recent progress in tuning and functionalizing MOFs to promote practical CWA removal under realistic battlefield conditions.

In this work, nitrite intercalated CaAl-LDH was firstly prepared in this work. Scanning electronic microscopy (SEM) coupled with the energy dispersive spectrometer (EDS) was used to characterize the morphology and element composition of the synthesized powder. Fourier transform infrared spectroscopy (FTIR) was used to characterize the chemical composition and X-ray diffraction (XRD) was used to analyze the structure. The nitrite release curve and the chloride concentration change curve were obtained to study the anion-exchange reaction. The corrosion protection effect of the CaAl-LDH loaded with nitrites towards the carbon steel was evaluated in 0.02 M NaCl solution by electrochemical impedance spectroscopy (EIS). Then the powder was added in the epoxy coating with a percentage of 2% (vs. epoxy resin). The coating morphology and roughness was evaluated by SEM and laser microscopy, and the corrosion protection effect was investigated by EIS in an immersion period of 21 d. Local electrochemical impedance spectra (LEIS) was used to characterize the corrosion development process in micro-corrosion sites. The corrosion product of the scratched area after salt spray exposure was analyzed by EDS and Raman spectroscopy. The corrosion protection mechanism of the CaAl-LDH loaded with nitrites was proposed based on the above experimental results.

;Yams are economic and medicinal crops with a long growth cycle, spanning between 9-11 months due to the prolonged tuber dormancy. Tuber dormancy has constituted a major constraint in yam production and genetic improvement. In this study, we performed non-targeted comparative metabolomic profiling of tubers of two white yam genotypes, (Obiaoturugo and TDr1100873), to identify metabolites and associated pathways that regulate yam tuber dormancy using gas chromatography-mass spectrometry (GC-MS). Yam tubers were sampled between 42 days after physiological maturity (DAPM) till tuber sprouting. The sampling points include 42-DAPM, 56-DAPM, 87DAPM, 101-DAPM, 115-DAPM, and 143-DAPM. A total of 949 metabolites were annotated, 559 in TDr1100873 and 390 in Obiaoturugo. 39 differentially accumulated metabolites (DAMs) were identified across the studied tuber dormancy stages in the two genotypes. 27 DAMs were conserved between the two genotypes, whereas, 5 DAMs were unique in the tubers of TDr1100873 and 7 DAMs were in the tubers of Obiaoturugo. The differentially accumulated metabolites (DAMs) spread across 14 major functional chemical groups. Amines and biogenic polyamines, amino acids and derivatives, Alcohols, flavonoids, alkaloids, phenols, esters, coumarins and phytohormone positively regulated yam tuber dormancy induction and maintenance, whereas, fatty acids, lipids, nucleotides, carboxylic acids, sugars, terpenoids, benzoquinones, and benzene derivatives positively regulated dormancy breaking and sprouting in tubers of both yam genotypes. Metabolite set enrichment analysis (MSEA) revealed that 12 metabolisms were significantly enriched during yam tuber dormancy stages. Metabolic pathway topology analysis further revealed that six metabolic pathways (linoleic acid metabolic pathway, phenylalanine metabolic pathway, galactose metabolic pathway, starch and sucrose metabolic pathway, alanine-aspartate-glutamine metabolic pathways and purine metabolic pathway) exerted significant impact on yam tuber dormancy regulation. This result provides vital insights into molecular mechanisms regulating yam tuber dormancy.

Sphalerite has been recognized as the most important carrier of critical metal of Indium (In) due to that In mainly exists in the sphalerite lattice by isomorphic substitution. There are two significant replacing schemes for In entry into sphalerite, these are, Ag++In3+→2Zn2+ and Cu++In3+→2Zn2+. In order to understand the reaction process and constraints of the two substitution schemes, this paper uses first-principles methods to calculate In and Ag, Cu replacing Zn in sphalerite. According to the substitution schemes of Ag++In3+→2Zn2+ and Cu++In3+→2Zn2+, two doped sphalerite systems of Zn30InAgS32 and Zn30InCuS32 were constructed using 2×2×2 supercell model of sphalerite. Firstly, the pressure is controlled to 30MPa, and the temperature is set from 20-40MPa to simulate the response of the two doped sphalerite systems to temperature; Then, the control temperature was unchanged to 600K, and the pressure was set from 20-40MPa to investigate the pressure control of the two doped sphalerite systems. The lattice parameters, substitution energy, electronic structure, and population analysis of the designed models before and after replacement have been critically compared. The main conclusions can be drawn that it is more stable for In to enter sphalerite via the coupled substitution scheme Cu++In3+→2Zn2+, and the conditions that the two substitution schemes most likely to occur are 650K and 40MPa. This study not only reveals the physical and chemical properties of In-rich sphalerite formed by the two reaction processes of Ag++In3+→2Zn2+ and Cu++In3+→2Zn2+, but also has a certain enlightenment effect on the search for indium in sphalerite, and promotes the application of first principles in mineralization analysis.

Here we draw insights from the latest serendipitous findings made on the opposing roles of a validated drug-target protein Keap1. We weigh up how natural reactive electrophiles and electrophilic small-molecule drugs in clinical use directly impinge on seemingly conflicting, yet both Keap1-electrophile-modification-dependent, cell-survival- vs. cell-death-promoting behaviors. In the process, we convey how understanding reactive chemical-signal regulation at a single-protein-specific level is an enabling necessity in deconstructing otherwise intricate reactive-small-molecule-responsive cellular pathways. We hope this opinion piece further spurs the broader interests of basic and pharmaceutical research communities toward better understanding of molecular mechanisms underpinning reactive small-molecule-regulated signaling subsystems.

This paper presents an extension of the results obtained in previous work concerning the application of global optimization techniques to the design of finite strategic games with mixed strategies. In that publication the Fuzzy ASA global optimization method was applied to many examples of synthesis of strategic games with one previously specified Nash equilibrium, evidencing its ability in finding payoff functions whose respective games present those equilibria, possibly among others. That is to say, it was shown it is possible to establish in advance a Nash equilibrium for a generic finite state strategic game and to compute payoff functions that will make it feasible to reach the chosen equilibrium, allowing players to converge to the desired profile, con- sidering that it is an equilibrium of the game as well. Going beyond this state of affairs, the present article shows that it is possible to ”impose” multiple Nash equilibria to finite strategic games by following the same reasoning as before, but with a fundamental change: using the same fundamental theorem of Richard McKelvey, modifying the originally prescribed objective function and globally minimizing it. The proposed method, in principle, is able to find payoff functions that result in games featuring an arbitrary number of Nash equilibria, paving the way to a substantial number of potential applications.

Reverse water gas shift reaction (RWGS) is an important process which plays a vital role in many CO2 utilization related reactions. Noble metals are the most active catalysts in RWGS, but the high price and low reserve strangled their applications. In the present work, we reported a non-transition-metal MgAl2O4 catalyst which showed outstanding activity and stability at high temperatures in the RWGS reaction and improved performance after doping of single atomic Nin+. The catalyst can obtain 46% of CO2 conversion in durability test of 75 h at 800 °C under high weight hourly space velocities (225 000 ml g-1 h-1). The adsorption sites, possible reaction route, and effects of Nin+ single atoms on the (111) surface of MgAl2O4 for RWGS were investigated by in situ DRIFTS and DFT calculations. The results indicated that the rate determining reaction step of RWGS on MgAl2O4 and Ni (SA)/MgAl2O4 were both the reaction of OH* + H* → H2O* + *, but the energy barrier was significantly reduced after introducing single atomic Nin+. Nin+ atoms can increase the hydroxyl coverage on the surface of catalyst and Al3+ sites near the Nin+ ion are considered as the predominant active sites for RWGS reactions.

Dermal wound healing describes the progressive repair and recalcitrant mechanism of damaged skin and eventually reformatting and reshaping the skin. Many probiotics, nutraceuticals, metal nanoparticles have been associated with improved healing process of intra and inter tissue wounds. Despite the vast nature on material based wound healing mediators, the exact mechanism on material-cellular interaction is still point of repent issue particularly in diabetics and pathological condition. The use of bioengineered alternative agents will likely only continue to dominate the outpatient and perioperative management of chronic, recalcitrant wounds as new additional products continue to cut costs and improve wound healing process. This review article provides an update of the various remedies with confirmed wound healing activities by a diverse group of agents from previous experiments conducted by various researchers

Anterior Cruciate Ligament (ACL) tear is currently a main issue in all of sports communities. Although the number of ACL injuries in football remains low, it’s consequences on both professional and personal lives remain a major concern of rehabilitation. If practitioners often require more time to bring athletes in the best condition, the fact remains that this concept of time before return to sport is nowadays considered as obsolete. Indeed, the better understanding of the mechanisms of lesion and the strains placed on the graft after reconstruction, allow us to establish a personalized program based on clinical criteria and the patient's objectives. The current scientific literature allows us today to optimize the return to play and performance by the use of neuromotor and neurocognitive approaches, muscle strengthening methods and a preventive program necessary to cover the previous level of the players while taking into account physiological and psychological changes due to ACL reconstruction. Indeed, it is important to have a systemic approach centered on the patient, the sports movement, as close as possible to the field in order to find an optimal function of the knee in interaction with its environment.If there is a risk of reinjury of the ACL, it appears important to be able to identify the risk factors so that the player can return to play in optimal conditions.

Bufadienolides-like chemicals, which mostly composed the active ingredient of Chansu, had been widely discovered to possess anti-inflammatory, tumor-suppressing and antipain activity, but the mechanisms of action were not clearly illuminated. In this research, in order to explore the potential mechanism of bufadienolides-like chemicals on breast cancer, a serious of bioinformatics analysis, included (1) differentially expressed genes identification combined with gene set variation analysis, (2) tissue specific co-expression network construction, (3) differentially regulated sub-networks detection with disease phenome, (4) hub gene selection and it’s relation to survival probability, and (5) similar small molecule detection were performed with gene expression profiles of bufadienolides-like chemicals. Results indicated bufadienolides-like chemicals had the most same target with valproic, estradiol and etc, could disturbed the pathways in RNA splicing, apoptotic process, cell migration, extracellular matrix organization, adherens junction organization, synaptic transmission, Wnt signaling, AK-STAT signaling, BMP signaling pathway and unfolded protein response, and had the potential ability to be used as anticancer, hormones and vasoprotectives agents.

Ginkgolic acids (GA) have been reported to exhibit anticancer properties, however, the mechanisms remain unclear. This study aims to investigate the mechanisms of GA C13:0 that was isolated from Ginkgo biloba exocarp (GBE) for anti-proliferation, pro-apoptosis and anti-migration effects in human MCF-7 and mouse 4T-1 breast cancer cells. The cytotoxic effect, apoptosis induction and migration inhibition were measured using MTT, TUNEL and Wound healing assays. The expression of mRNA and protein were determined using qPCR and Western blot. Our results showed that no cytotoxicity was found at concentrations of C13:0 below 100µM. The effects of GA C13:0 was further demonstrated by up-regulation of the Bax/Bcl-2 apoptosis pathway and the expression of Apaf-1 protein in the mitochondria. In addition, GA C13:0 also suppressed cell migration and epithelial to mesenchymal transition (EMT) with the increase of E-cadherin expression accompanied by the decrease of Snail, MMP-2, MMP-9 and Vimentin expression. Moreover, GA C13:0 induced cytochrome P450 (CYP) 1B1 expression in aryl hydrocarbon receptor (AhR) pathway. Notably, the up-regulation of CYP1B1 also might play a pivotal regulatory role in mitochondrial and EMT pathways in MCF-7 and 4T-1 cells. Our results may have implications for the development of anticancer agents containing GA as functional additives.

In some sour reservoirs and tertiary oil recovery blocks, SO₄^2- in solution can cause the corrosion and corrosion fatigue of the sucker rods. In this paper, the corrosion behaviors of super-strength sucker rod FG20 (16Mn2SiCrMoVTiA) steel in the well fluid are investigated by electrochemical measurements, and electron probe micro-analyzer (EPMA) analysis. The results show that FG20 steel has a favorable corrosion resistance in neural solutions. When the hydrogen ion content increases, the hydrolysis of SO₄^2- greatly accelerates the corrosion of FG20 steel. The energy dispersive X-ray(EDX)results demonstrate that the corrosion process of FG20 steel in neural well liquid is an oxygen concentration process, and the protective FeCO₃ and Fe₂O₃ on the surface of the samples can prevent further corrosion. With the increase of the acidity in the well liquid, the corrosion process converts into a sulphide concentration process, and the sloppy FeS and mackinawite film cannot provide effective protection for the specimens, resulting in the increase of corrosion rate.

In this work, kinetics of the reaction between 5,10,15,20-tetrakis(N-methylpyridium-4-yl)porphyrin and Ni2+ species were investigated in aqueous solution at 25 ±1 ºC in I = 0.10 M (NaNO3). Speciation of Ni2+ was carried out in I = 0.10 M (NaNO3) in order to provide the distribution of the Ni2+ species with different solution pH. The experimental data have been compared with the speciation diagram constructed from the values of hydrolysis constants of Ni2+ ion. Speciation data showed that the hexaaquanickel(II), [Ni(H2O)6]2+, ions take place in hydrolysis reactions through formation of [Ni(OH2)6-n(OH)n]2-n species with solution pH. Based on the speciation of Ni2+ and pH dependent rate constants, rate expression can be written as: d[Ni(TMPyP)4+]/dt = (k1[Ni2+(aq)] + k2[Ni(OH)+(aq)] + k3[Ni(OH)2o(aq)] + k4[Ni(OH)3-(aq)])[H2TMPyP4+], where k1, k2, k3 and k4 were found to be k1 = (0.62 ± 0.22) × 10-2; k2 = (3.60 ± 0.40) × 10-2; k3 = (2.09 ± 0.52) × 10-2, k4 = (0.53 ± 0.04) × 10-2 M-1s-1 at 25 ±1 °C, respectively. Kinetic results showed that monohydroxo, [Ni(H2O)5(OH)]+, is the most reactive among the [Ni(OH2)6-n(OH)n]2-n species. The enhanced reactivity has been ascribed to the formation of hydrogen bonding between oxygen atom of hydroxyl group of the [Ni(H2O)5(OH)]+ species and the pyrrolic hydrogen atom of the [H2TMPyP]4+. The rate of formation of [Ni(II)TMPyP]4+ complex was to be 3.99 × 10-2 M-1s-1 in I = 0.10 M, NaNO3 (25 ± 1 ºC). Ionic strength effect on the reaction rate is suggested that the net charge of the tetracationic porphyrin is to be +3.6 on the basis of Brønsted-Bjerrum equation. The UV-Vis and fluorescence data revealed that [Ni(II)TMPyP]4+ and H2(TMPyP)4+ interact with DNA, and UV-Vis results suggest that Ni(II)-porphyrin and free base porphyrin interact with DNA via outside binding with self-stacking and intercalation, respectively. Mechanism of kinetics of formation of the [Ni(II)TMPyP]4+ complex in aqueous medium is discussed. An investigation of application of the [Ni(II)TMPyP]4+ complex along with other metalloporphyrins such as Zn2+-, Ru2+-, Pt2+-, [Au(III)TMPyP]5+ as anti-COVID-19 agents is now in progress under international collaboration.

There is scientific consensus that organismal aging did not evolve by natural selection (NS) because it lacks individual benefit. Nonetheless it exists, leading to much speculation about its origins, and when the diminishing force of selection begins. Both concepts are based upon two misconceptions; that aging occurs in and of itself and is caused by the declining strength of NS during the reproductive lifespan. Although lacking individual benefit, aging evolved by NS as a tradeoff of survival for reproduction. Based upon regulatory dynamics that participate in this tradeoff, aging begins once reproductive success has been achieved through offspring nurturing. Thereafter, the strength of NS wanes to exponentially accelerate aging, leading to death. Assumptions of the theory are that: (1) a life-long, “holistic” regulatory mechanism whose genic expression is modified epigenetically, originates in ontogenesis; (2) the regulatory mechanism of the last developmental stage becomes redundantly expressed during “morphostasis”, a non-aging, life interval of peak vitality to ensure completion of reproduction through nurturing, and (3) thereafter, loss of regulatory redundancy causes aging which reduces the strength of natural selection and allows accumulation of randomly occurring somatic damage.

Alkyl moieties—open chain or cyclic—are common in drug molecules and can be internal or terminal. The open-chain alkyls can be linear or branched; the cyclic alkyls may be substituted. Usually, the branches in open-chain alkyls and substituents in cycloalkyls influence both the pharmacokinetics and pharmacodynamics of a drug molecule. The hydrophobicity of alkyl moieties in drug molecules is modified by metabolic hydroxy functionalization via free-radical intermediates to give primary, secondary, or tertiary alcohols depending on the class of the substrate carbon. The hydroxymethyl groups resulting from the functionalization of methyl groups are mostly oxidized further to carboxyl groups to give carboxy metabolites. As observed from the surveyed cases in this review, hydroxy functionalization leads to loss, attenuation, or retention of pharmacologic activity with respect to the parent drug. On the other hand, carboxy functionalization leads to a loss of activity with the exception of only a few cases in which activity is retained. The exceptions are those groups in which the carboxy functionalization occurs at a position distant from a well-defined primary pharmacophore. Some parent-drug equiactive hydroxy metabolites have been developed into metabolite ester prodrugs, while some of the parent-drug carboxy metabolites have been developed into metabolite drugs. In this review, we present and discuss the above state of affairs for a variety of drug classes, using selected drug members to show the effect on pharmacologic activity as well as dependence of the metabolic change on drug molecular structure. Some subtexts found to manifest from the hydroxy and carboxy functionalization of alkyl moieties in drug molecules are presented and discussed. The review provides basis for informed predictions of (i) structural features required for metabolic hydroxy and carboxy functionalization of alkyl moieties in existing or planned small drug molecules; and (ii) whether the resulting metabolites will possess pharmacologic activity or be devoid of it.

Five-day exposure of clary sage (Salvia sclarea) to 100 μM cadmium (Cd) in hydroponics was sufficient to increase Cd concentrations significantly in roots and aboveground parts and affect negatively whole plant levels of calcium (Ca) and magnesium (Mg), since Cd competes for Ca channels, while reduced Mg concentrations are associated with increased Cd tolerance. Total zinc (Zn), copper (Cu), and iron (Fe) uptake increased but their translocation to the aboveground parts decreased possible due to translocation barriers. Despite the substantial levels of Cd in leaves, without any observed defects on chloroplast ultrastructure, an enhanced photosystem II (PSII) efficiency was observed, with a higher fraction of absorbed light energy to be directed to photochemistry (ΦPSΙΙ). The concomitant increase in the photoprotective mechanism of non-photochemical quenching of photosynthesis (NPQ) resulted in an important decrease in the dissipated non-regulated energy (ΦNO), modifying the homeostasis of reactive oxygen species (ROS), through a decreased singlet oxygen (1O2) formation. Thus, when clary sage was exposed to Cd for a short period, tolerance mechanisms were triggered, with PSII photochemistry to be regulated by NPQ in such a way that PSII efficiency to be enhanced. However, exposure to a combination of Cd and high light or for longer duration (8 days) to Cd alone, resulted in an inhibition of PSII functionality pointing out towards Cd toxicity. Thus, the rapid activation of PSII functionality at short time exposures and the inhibition at longer duration suggests a hormetic response and describes these effects in terms of “adaptive response” and “toxicity”, respectively.

The effectiveness of a recently proposed methodology in the identification of damage in planar, multi-storey, Reinforced Concrete (RC) moment-frames, which develop a plastic-yield mechanism on their beams, is showcased here via the examining of a group of such existing multi-storey frames with three or more unequal spans. According to the methodology, the diagram of the instantaneous Eigen-Frequencies of the frame in the nonlinear regime is drawn as a function of the inelastic seismic roof displacement by performing a sequence of pushover and instantaneous modal analyses with gradually increasing target displacement. Using this key-diagram, the locations of severe seismic damage in an existing moment-frame can be evaluated if the instantaneous fundamental eigen-frequency of the damaged frame, at an analysis step within the nonlinear area, is known in advance by “the monitoring and the identification of frequencies” using a local network of uniaxial accelerometers. This is a hybrid technique because both procedures, the instrumental Monitoring of the structure and the Pushover analysis on the frame (M and P technique), are combined. Moreover, the damage image of the planar multi-storey moment-frame is illustrated, and the lateral stiffness matrix of the damaged frame is calculated with high accuracy.

The Huichang fault Basin in Jiangxi Province exhibits high terrestrial heat flow values and a dense concentration of hot springs. However, existing research is limited to individual geothermal fields without a comprehensive basin-wide analysis of geothermal water origins. This study investigates the source of geothermal water across five representative geothermal fields using hydrochemical components and isotopic analyses. The findings indicate: (1) The hydrochemical type transitions from bicarbonate sulphate-sodium-calcium in the north to bicarbonate sodium-calcium in the south; (2) Major chemical components of the geothermal water derive from evaporative salt rocks (Cretaceous sand conglomerate cover) and siliceous formations (granite/metamorphic rock basement); (3) The recharge elevation for geothermal water is approximately 1 km, sourced from adjacent hills. The central basin's geothermal water has an apparent age of about 26,000 years, with δ¹³C indicating participation in deep circulation; (4) Thermal reservoir temperatures range from 74 to 113℃, with the lowest temperatures at the basin's edges (Anzishan and Shangjin geothermal fields) and higher temperatures towards the center, suggesting increased warming and a circulation depth of 1.5 to 2.5 km; (5) Simulation results of reverse water-rock interaction indicate that mineral precipitation-dissolution processes are governed by the basin's main thermal control structures. The geothermal fields are predominantly influenced by reduction alterations associated with granite and are closely linked to paleo-geothermal waters in the enclosed basin, with the formation of these fields heavily reliant on the heat production or conduction from radioactive elements in granite.

It is desirable to upgrade previous evolutionary theories, which have remained incomplete and controversial for decades. Here we employ the concept of carbon-based entities (CBEs), which include methane, amino acids, proteins, organisms, and other entities containing relatively many carbon atoms. We deduce the driving force, mechanisms, steps, modes, tempos of CBE evolution, through integration of biology, physics, and chemistry using logics for complex issues. We hence establish the Carbon-Based Evolutionary Theory (CBET). The CBET suggests that evolution is the increase in hierarchy, diversity, fitness of CBEs under natural selection and driven by thermodynamics due to the chemical effect of the thermodynamic features of the Earth on CBEs. It provides better explanations for life origin, macroevolution events, natural selection, sympatric speciation, and evolution tempos than previous evolutionary theories. It reveals the evolutionary basis of multiple important social notions, including diversity, collaboration, altruism, obeying rules, and proper increase in freedom. It refutes some wrong notions in thermodynamics, including negative entropy (negentropy) and that biological order is equal to thermodynamic order, which have misled many people. The CBET is supported by its deduction and application. It could be a rare bridge linking laws of thermodynamics, evolution of life, and development of human society, and could have great significance in various sciences.

The loose and porous structure and abundant pores of biochar provide conditions for being a suitable fertilizer carrier. Biochar loaded with beneficial microorganisms will greatly promote plant growth and soil improvement. In this work, an environmentally friendly Paenibacillus mucilaginosus loaded biochar-based fertilizer (B@PM) with high nutrient content, good slow-release effect and increased biological activity was prepared. The released mechanism of P-K-Ca from B@PM and the synergistic effect on the soil nutrients and plant growth were also analyzed. The experimental results showed that the release behavior of P, K and Ca from B@PM was diffusive and dissolved, which conforms to the Power function and Parabolic diffusion models, respectively. The potting experiment showed that the root length (30.77%), leaf width (71.67%), and plant height (81.08%) of Chinese cabbage were enhanced after the application of B@PM, and the organic matter, available phosphorus, available potassium, and total calcium in the soil were also substantially enhanced. In addition, the abundance of the Proteobacteria, Actinobacteria, Bacteroidetes and Firmicutes in the in the rhizosphere soil was increased, as well as the activities of catalase (82.84%) and alkaline phosphatase (39.64%). The results of RDA analyses showed that B@PM increased the content of the environmental factors, such as OM, URE, EC, TCa, AK, CAT, AP and ALP, thus improving soil quality and plant length.

In order to study the key factors that induce green travel among urban residents under the carbon inclusive mechanism, analyze the formation mechanism of green travel intention and reduce urban transportation carbon emissions. First, an SEM model of urban residents’ green travel under the carbon inclusive mechanism was constructed (the 8 latent variables including Subjective Norms (SN), Attitude (ATT), Perceived Behavioral Control (PBC), Habits (HAB), Perceived Usefulness (PU), Perceived Ease of Use (PEU), Continuous Intention of Carbon Inclusive Platform application (CI), Behavioral Intention (BI)). Then, based on the data analysis and path analysis results of 354 valid sample data obtained through online surveys, the interrelationships and corresponding parameters between latent variables and manifest variables were obtained. The results show that SN, ATT, PBC, HAB, PU, PEU and CI all have varying degrees of effects on BI. Among them, in the direct influence relationship, the influence path coefficients of CI, PBC and ATT on BI are 0.529, 0.299 and 0.146 respectively; The influence coefficient of HAB on BI is 0.152, but P>0.05, it fails the test, so the influence of HAB on BI is Not significant; in the indirect impact relationship, the coefficient of HAB indirectly affecting BI through ATT is 0.102, and the coefficient of PU indirectly affecting BI through CI and SN is 0.450. It can be seen that under the carbon inclusive mechanism, useful methods such as increasing the value of carbon points and the breadth of application, improving perceived behavioral control, increasing publicity and social awareness, and cultivating green travel attitudes can promote the willingness of urban residents’ green travel behavioral intention.

As the global arid climate intensifies and the groundwater becomes increasingly scarce, drought stress has become a major challenge to plant growth and development worldwide, especially causing yield reduction and extinction of cultivated crops. In a large number of drought resistance studies, DNA methylation has been found dynamically associated with response to drought stress in plants by regulating gene expression and developments in plants, but the specific mechanisms are not yet clear. In this article, the current advances of research have been summarized on DNA methylation response to drought stress in various plant species, in terms of methylation detection methods, mechanisms of pattern changes (DNA de novo methylation, DNA maintenance methylation, and DNA demethylation), and its response to drought stress. With Most of the studies showed significant changes in genome or gene promoter methylation levels in plants subjected to drought stress, but the identification of the genes and pathways involved is still in the minority. The aim is to provide references for in-depth research on the response of plants to drought stress through epigenetics, and to uncover drought resistance genes regulated by DNA methylation, specific signaling pathways, and molecular mechanisms of action.

The multi-objective optimization design of hydraulic climbing mechanism (the core mechanism of gantry crane) was realized by using the method of combining central composite design (CCD), Kriging and multi-objective genetic algorithm (MOGA). Firstly, the hydraulic climbing mechanism model was established and the appropriate design variables were selected. The mass, maximum deformation and maximum equivalent stress of the hydraulic climbing mechanism was taken as the optimization objectives. Through the comparative analysis of the parameters of wedge block, anchor block, anchor plate、baffle, the parameters that have the greatest impact on the optimization objectives are selected as geometric constraints. Then, according to the results of experimental design, Kriging model was used to establish the response surface optimization model of objective function. Finally, the optimal results were obtained by using MOGA method. The experimental results show that the optimization strategy is reliable, and the mass of the optimized model is reduced by 10.28%. While meeting the actual production requirements, the lightweight design of the hydraulic climbing mechanism is realized, which saves the design cost and improves the material utilization rate.

Rare earth elements (REEs) are a type of new material resources, which have attracted significant attention in recent years. REEs have emerged as essential metals in modern-day technology due to their unique functions. Long-term large-scale mining and utilization of rare earths have caused serious environmental pollution and constitutes a global health issue, which raised concerns about human health safety. However, the toxicity profile of suspended particulate matter of REEs in the environment interacts with the human body in remain largely unknown. Studies have shown that REEs can enter the human body through a variety of pathways, leading to a variety of organ and system dysfunctions through changes in genetics, epigenetics, and signaling pathways. Through an extensive literature search and critical analysis, we provide a comprehensive overview of the available evidence, identify knowledge gaps, and make recommendations for future research directions.

Hydrogen is considered as an ideal substitute to the traditional fossil fuels because of its widespread sources, high calorific value of combustion, and zero carbon emissions. The electrocatalytic water-splitting to produce hydrogen is also deemed to be the best approach, however, it is a challenge to make high-efficient and low-cost electrocatalysts. Single-atom catalysts (SACs) are considered the most promising candidate to replace the traditional noble-metal catalysts. Compared with SACs, the dual-atom catalysts (DACs) are of greater attraction including higher metal loading, more versatile active sites, and excellent catalytic activity. In the review, several general synthetic strategies and structural characterization methods of DACs are introduced, and the mechanisms of hydrogen evolution reaction (HER) and oxygen evolution reactions (OER) are discussed. The authors hope that the review has given some insights and inspiration to the researchers about DACs in electrocatalytic water-splitting.

The study of dog point following has been increasingly popular, at least partially due to the initial claims that dogs outperform apes and the suggestion that our domestication process caused dogs to have a biological capacity to communicate with humans. We take the view that dog pointing is more complicated than was initially reported, and in this study, we explore several potential variables that may make a difference. Our variables include point type (ipsilateral (same-side) vs contralateral (cross-body) points), position (standing vs seated), and distance (proximal vs distal). We find that most dogs follow ipsilateral points while less than half of the dogs in our sample follow contralateral points, and that position and distance also affect dogs’ success. We suggest that dogs acquire ipsilateral points via associative mechanisms, but that contralateral points require the dogs to understand the humans’ communicative intent.

To ensure the security of highly sensitive remote sensing images (RSI) during their transmission, it is essential to implement effective content security protection methods. Generally, secure distribution schemes for remote sensing images often employ cryptographic techniques. However, sending encrypted data exposes communication behavior, which poses significant security risks to the distribution of remote sensing images. Therefore, this paper introduces deep information hiding to achieve secure distribution of remote sensing images, which can serve as an effective alternative in certain specific scenarios. Specifically, the Deep Information Hiding for RSI Distribution (hereinafter referred to as DIH4RSID) based on encoder-decoder network architecture with Parallel Attention Mechanisms (PAM) by adversarial training was proposed. Our model is constructed with four main components: a preprocessing network (PN), an embedding network (EN), a revealing network (RN) and a discriminating network (DN). The PN module is primarily based on Inception to capture more details of RSI and targets of different scales. The PAM module obtains features in two spatial directions to realize feature enhancement and context information integration. The experimental results indicate that our proposed algorithm achieves relatively higher visual quality and secure level compared to related methods. Additionally, after extracting the concealed content from hidden images, the average classification accuracy is unaffected.

The centrifugal force field in the hydrocyclone was affected by the concave-wall curvature radius R0, the mechanism of droplet deformation was closely related to the mass transfer efficiency. Numerical simulation and experimental data were collected to reveal the deformation characteristics and mechanism of single droplet crossing concave-wall jet. Normalized interfacial energy γ and stretching performance were provided to investigate the droplet deformation process. The results showed that the droplet was stretched along the streamwise and shrank along the spanwise in the concave-wall jet. The droplet interfacial energy and deformation were the largest when the droplet crossed the jet boundary at t = 0.20 s. Maximum γ value increased with the increase of R0 by 57.3% to 71.4%, and the distance between droplet and concave-wall increased with R0. Q-criterion was exported to show the vortex strength increasing as the decrease of R0 in the jet boundary. The pressure distribution inside the droplet showed that the pressure decreased as R0 increased, while the pressure difference increased along the streamwise and wall-normal direction. The study suggested that the droplet breakup was more difficult for the smaller R0, which was beneficial for liquid-liquid heterogeneous separation.

Aircraft heat exchangers play a crucial role in maintaining thermal balance and ensuring that essential components operate efficiently and safely. In this context, it is highly relevant to gain knowledge about the deterioration and the predominant damage mechanisms of these components. In this study, two different non-destructive methods are employed to analyze the damage initiation of a heat exchanger part during fatigue test. On the one hand, Acoustic Emission technique is employed using membrane-free microphones capable of capturing a broad bandwidth. The acoustic events were classified by a machine learning algorithm to determine their source and damage mechanisms. On the other side, Digital Image Correlation (DIC) allowed the measurement of the strain evolution along the test and more precisely, redistributions were considered as damage indicators. As a result, it was identified that AE served as early damage indicator as the cumulative number of events was in good agreement with the severity of the damage. With respect to classification two clear clusters ascribed to different type of events were identified. In the case of DIC, strain redistributions gave clear indications of damage or deterioration but at a later stage compared to AE

With the global increase of photovoltaic (PV) modules deployment in recent years, the need to explore and realize their reported failure mechanisms has become crucial. Despite PV modules being considered reliable devices, failures and extreme degradations often occur. Some degradations and failures can be minor and cause no critical harm if within the expected range. Others, may start mildly and then deteriorate faster to become catastrophic, especially in harsh environments. This paper conducts a state-of-the-art literature review to scan PV failures, types, and their root cause based on PV’s constructed components (from protective glass to junction-box). It outlines the hazardous consequences beyond PV module failures, describing what harm they can bring to the PV system. As we delve into the literature, it becomes clear that every component is vulnerable to certain types of failures; some can deteriorate within themselves, and others infect further PV components resulting in emerging more severe failures. In the end, the review briefly summarises PV failure detection techniques, emphasising electrical characterization techniques, and disclosing the need to engage more electrical parameters. Most importantly, this review can prepare the stage for the PV research community to identify the most prevalent degradation processes. This, in turn, encourages researchers to investigate them throughout modelling and experimental studies to forecast them at the early onset in order to protect the PV systems from hazardous malfunctions.

This study investigates the microstructures and deformation mechanism of hetero-structured pure titanium under different high strain rates (500 s-1，1000 s-1，2000 s-1). The influence of strain rate on the deformation mechanism is examined. As the strain rate increases, the dominance of dislocation slip decreases while deformation twinning becomes more prominent. Notably, at a strain rate of 2000s-1, nanoscale twin lamellae are activated within grain with a size of 500nm, which is a rarely observed phenomenon in pure Ti. Additionally, martensitic phase transformation is also identified. These findings can greatly enhance our understanding of the mechanical responses of Ti and broaden the potential applications of Ti in dynamic deformation scenarios.

Electrocatalytic and photocatalytic hydrogen evolution reaction (HER) provides a promising approach to clean energy generation. Bimetallic single-atom catalysts raised and have been explored to be advanced catalysts for HER. It is urgent to review and summarize the recent advances in developing bimetallic single-atom HER catalysts. Firstly, the fundamentals of bimetallic single-atom catalysts are presented, highlighting their unique configuration of two isolated metal atoms on supports and resultant synergistic effects. Secondly, recent advances in bimetallic single-atom catalysts for electrocatalytic HER under acidic/alkaline conditions are then reviewed, including W-Mo, Ru-Bi, Ni-Fe, Co-Ag, and other dual-atom systems on graphene and transition metal dichalcogenides (TMDs) with enhanced HER activity versus monometallic analogs due to geometric and electronic synergies. Then, Photocatalytic bimetallic single-atom catalysts on semiconducting carbon nitrides for solar H2 production are also discussed. Finally, an outlook is provided on opportunities and challenges in precisely controlling bimetallic single-atom catalyst synthesis and gaining in-depth mechanistic insights into bimetallic interactions.

Crossostephium chinense is a wild species with strong salt tolerance, which has great potential to improve the salt tolerance of cultivated chrysanthemums. Conversely, the unique salt-tolerant molecular mechanisms of Cr. chinense are still unclear. This study performed a comparative physiological and transcriptome analysis of Cr. chinense, Chrysanthemum lavandulifolium and their hybrids. The physiological results showed that Cr. chinense maintained a higher superoxide dismutase (SOD) activity, to alleviate the oxidative damage to membrane. KEGG enrichment analysis showed that the plant hormone signaling transduction and the MAPK signaling pathway were mostly enriched in Cr. chinense and hybrids under salt stress. Further weighted gene co-expression network analysis (WGCNA) of DEGs suggested that the abscisic acid (ABA) signaling transduction may play a significant role in the salt-tolerant mechanisms of Cr. chinense and hybrids. The tissue-specific expression patterns of the candidate genes related to ABA signaling transduction and MAPK signaling pathway indicated that genes related to ABA signaling transduction performed significant expression levels under salt stress. This study provides a theoretical foundation for future research into the molecular mechanism of salt tolerance in chrysanthemums under salt stress.

In this paper we will provide a new equation that explains why there are three generations or families of leptons and quarks, respectively. We will also explain why all those particles have the known mass ratios amongst their three respective generations and flavors. We will also tackle the problem of Yukawa couplings being arbitrary parameters in the Standard Model Higgs mechanism, which is a long standing problem do to their formulaic dependence on the Higgs Vacuum Expectation Value (VEV). We will attempt to solve this problem and provide a strong argument through an equation for Yukawa couplings of all leptons and quarks via a new methodology that depends on the running of the fine-structure constant on the Q scale, quantum numbers and the Weinberg angle (also on the Q scale). We will also make predictions for all three left-chiral neutrino mass eigenstates and we will provide upper limits for the three right-chiral neutrino mass eigenstates

The diverse physical appearances and wide density range of polymer bead foams offer immense potential across various applications and future advancements. The multi-scale and multi-level structural features of bead foams involve many fundamental scientific topics. This review presents a comprehensive overview of recent progress in bead foams preparation and molding techniques. Initially, a comparative analysis is conducted among bead foam characteristics of distinct polymers, based on their unique properties. Subsequently, a summary and comparison of molding processes employed for fabricating bead foam parts are provided. Beyond traditional methods like steam-chest molding (SCM) and adhesive-assisted molding (AAM), emerging techniques like in-mold foaming and molding (IMFM) and microwave selective sintering (MSS) are highlighted. Lastly, the bonding mechanisms behind the diverse molding methods are discussed.

Fused silica glass is a material with outstanding mechanical, thermal and optical properties. Being a brittle material, it is challenging to shape. In the last decade, the manufacturing of monolithic flexible mechanisms in fused silica has evolved with the femtosecond laser-assisted etching process. However, instrumenting those structures is demanding. To address this obstacle, this article proposes to inscribe a Bragg Grating sensor inside a flexure and interface it with an optical fibre to record the strain using a spectrum analyzer. The strain sensitivity of this Bragg Grating sensor is characterized at 1.2 pm/μϵ (1 μϵ = 1 microstrain). Among other applications, deformation sensing can be used to record a force. Its use as a micro-force sensor is estimated. The sensor resolution is limited by our recording equipment to 30 μN over a measurement range above 10 mN. This technology can offer opportunities for surgery applications or others where precision and stability in harsh environments are required.

Real-time tracking is one of the most challenging problems in computer vision. Most Transformer-based trackers usually require expensive computational and storage power, which leads to the inability of these robust trackers to achieve real-time performance in resource-constrained devices. In this work, we propose a lightweight tracker, AnteaTrack. To localize the target more precisely, we develop a scaling-invariant max-filtering operator employing a sliding window combined with local max-pooling, which filters out the suspected target from the feature and performs an augmented representation while suppressing the background. For a more tight bounding box, we employ Pixel-Shuffle to increase the resolution of the feature map and get a more fine-grained representation of the target. In addition, AnteaTrack can run in real-time at 47 frames per second(FPS) on the CPU. We tested AnteaTrack on 5 datasets, and a large number of experiments have shown that AnteaTrack provides the most efficient solution compared to the same type of CPU real-time trackers. The code will be available at https://github.com/cnchange/AnteaTrack.

Fifty-two kinds of N’-phenylhydrazides were successfully designed and synthesized. Their anti-fungal activity in vitro against five strains of C. alb. was evaluated. All prepared compounds owned varying degrees of activity and their MIC80, TAI, and TSI values were calculated. The in-hibitory activities of 27/52 compounds against fluconazole-resistant fungi C. alb. 4395 and C. alb. 5272 were much higher than those of fluconazole. The MIC80 values of 14/52 compounds against fluconazole-resistant fungus C. alb. 5122 were less than 4 μg/mL, so it was the most sensitive fungus (TSIB = 12.0). A11 showed the highest inhibitory activity against C. alb. SC5314, 4395, and 5272. The antifungal activities of B14 and D5 against four strains of fluconazole-resistant fungi were higher than those of fluconazole. The TAI values of A11 (2.71), B14 (2.13), and D5 (2.25) are the highest. Further exploring the antifungal mechanism revealed that the fungus treated with compound A11 produced free radicals and reactive oxygen species, and their mycelium mor-phology was damaged. In conclusion, the hydrazide scaffold showed potential in the develop-ment of antifungal lead compounds. Among them, A11, B14, and D5 demonstrated particularly promising antifungal activity and hold potential as novel antifungal agents.

Adipose tissue has acquired considerable importance due to its role in maintaining body homeostasis. Beyond storing energy, adipose tissue is essential in numerous processes of energy metabolism, food intake, endocrine and immunological functions as well as neromodulatory functions by secreting hormones that participate in the regulation of homeostasis and being responsive to soluble proteins secreted by other tissues. An imbalance of these functions will generate structural and functional changes in the adipose tissue, favouring the secretion of deleterious adipocytokines that benefit a pro-inflammatory state, allowing the development of metabolic and cardiovascular diseases. Obesity is a disease that has increased rapidly in recent decades and is caused by environmental, hormonal, and genetic factors, which probably work in combination. Environmental factors that contribute to the increase in obesity include decreased physical activity, associated with increased screen time, increased accessibility and consumption of foods rich in fats and sugars. Weight loss should be recommended for all obese patients and overweight patients with comorbidities. For many patients who need to lose weight for medical reasons, the initial goal is to lose 5-10% of their body weight in the first 6 months. A common theme worldwide has been the development of professional guidelines for the control and treatment of obesity and in Chile, the Chilean Society of Metabolic and Bariatric Surgery led the process of adopting the adult obesity clinical practice guideline, which establishes changes in the approach to managing obesity as a chronic disease, with an emphasis on multifactorial lifestyle interventions that include dietary changes, increased physical activity, and behavioural modifications. Pharmacotherapy, medical devices, and bariatric surgery are other options for patients who need additional interventions, so the objective of this review is to know the pathophysiological mechanisms of obesity from its origin to the current treatments available for treatment.

This study investigates uranium solvent extraction under AMEX process conditions. The use of pure extractants without diluents or phase modifiers allows not only to reduce the use of volatile organic compounds, but also to provide higher extraction yields without third phase formation. Pure extractants are protonated amines or quaternary ammoniums with suitable counter ion, which act at the interface between ion pairs and protic ionic liquids. The mixture of sulfates anion (SO42-) and bis(trifluoromethanesulfonyl)imide anion (NTf2-) revealed unexpected nonlinear extraction behaviors, which appear highly important to rationalize for optimized application. Spectroscopic analysis (NMR, UV-vis, FT-IR, and EXAFS) showed that uranium extraction occurs via protonated amine and three sulphates. Nonlinear extraction could further be interpreted by considering water and acid transfer between the two phases: at lower sulphate ratios, the release of acid from the organic phase into the aqueous phase was shown to influence the number of protonated amines in the organic phase, affecting uranium extraction before its enhancement. Furthermore, the extraction loss at higher sulphate ratios, was assigned to the destabilization of bidentate uranium-sulphate complexes due to a competition between water and sulphates.

This paper proposes a multimodal fusion 3D target detection algorithm based on the attention mechanism to improve the performance of 3D target detection. The algorithm utilizes point cloud data and information from camera. For image feature extraction, the ResNet50+FPN architecture extracts features at four levels. Point cloud feature extraction employs the voxel method and FCN to extract point and voxel features. The fusion of image and point cloud features is achieved through regional point fusion and regional voxel fusion methods. After information fusion, the Coordinate attention mechanism and SimAM attention mechanism extract fusion features at a deep level. The algorithm's performance is evaluated using the DAIR-V2X dataset. The results show that compared to the Part-A2 algorithm, the proposed algorithm improves the mAP value by 7.9% in BEV view and 7.8% in 3D view at IOU=0.5 (cars) and IOU=0.25 (pedestrians and cyclist). At IOU=0.7 (cars) and IOU=0.5 (pedestrians and cyclist), the mAP value of the SECOND algorithm is improved by 5.4% in the BEV view and 4.3% in the 3D view, compared to other comparison algorithms.

Considering that consumers are more willing to buy products online, companies are increasingly selling remanufactured products online through e-commerce platforms. Notwithstanding the high attention it elicits from researchers and companies, the study about the remanufacturing trading platform is in its infancy. Thus, we investigate 20 remanufacturing trading platforms related nowadays and make a gap analysis among them in terms of: (i) business model, (ii) product display, (iii) delivery products, (iv) quality assurance and after-sales service, (v) product review and star rate and (vi) transaction and payment. On this basis, we analyze features and trends for the development of remanufacturing trading platforms and propose six key applications aimed at filling the identified gaps. The consortium blockchain has the characteristics of security and transparency, high credibility, traceability and unfalsifiability, low cost, and strong scalability, which can provide effective support for the six key applications. Then, we construct the technical framework and the model of a consortium blockchain-supported remanufacturing trading platform. Further, we analyze the coupling mechanism between consortium blockchain and remanufacturing trading platform to explain how the remanufacturing trading platform supported by consortium blockchain achieves development characteristics. This study provides important guidance for the development, construction, and operation management of remanufacturing trading platforms.

Dye wastewater containing bisphenol A (BPA) and dyes as pollutants have not been adequately studied. Our previous study revealed that thermoplastic polyurethane (TPU) nanofiber membranes (NFMs) modified by the addition of polyethyleneimine (PEI) and polydopamine (PDA) satisfactorily adsorb dyes. Herein, we first optimized the synthesis conditions for such membranes, noting a PEI:PDA monomer ratio of 2:2 and a deposition time of 48 h to be optimal. Experiments using these membranes revealed that binary systems containing BPA and the dyes (Congo red (CR), Eosin yellow (EY), or sunset yellow (SY)) exhibit three adsorption behaviors. CR and BPA compete with each other for adsorption sites, decreasing the maximum adsorption capacity (Qmax) for CR 208.3 mg/g (in a monomeric system) to 182.4 mg/g, whereas for BPA, it decreased from 26.7 to 22.8 mg/g. The adsorption rates for CR and BPA decreased from 0.002 min−1 and 0.331 min−1 in the monomeric systems to 8.37 × 10−4 min−1 and 0.072 min−1, respectively, in the binary CR–BPA system, exhibiting antagonistic effects. When EY and BPA coexist, Qmax for EY increased from 60.0 (monomeric) to 71.9 mg/g, whereas that for BPA increased from 35.6 to 43.2 mg/g, showing a synergistic effect due to the possible bridging effect. The adsorption sites for SY and BPA are independent of each other. Thus, PDA/PEI TPU NFMs exhibit the potential for removal of dye–BPA composites, whereas binary systems containing BPA with different dyes are adsorbed differently.

To solve the problem of smooth switching between car-following model and lane-changing model, the Intelligent Driver Model (IDM) for a single lane was used to study the driver's behavior switching mechanism of normally following, generating intentions to change lanes, creating space and speed gains, and performing lane change. In the case of sufficient lane-changing space and speed gains, the ego vehicle's intention to change lane was considered to solve the switching boundary between car-following behavior and lane-changing behavior, which is also the IDM failure point. In the event that there is no lane-changing gains, the IDM was optimized by incorporating the constraint components of the target lane vehicles in conjunction with the actual motion state of the ego vehicle, and the Stepless Switching Intelligent Driver Model (SSIDM) was constructed. Drivers' natural driving information was collected and scenario mining was performed on structured roads. On the basis of the collected data, an elliptic equation was used to fit the behavior switching boundary, and the two component balance coefficients of the front and rear vehicles on the target lane were identified. According to the test set verification results, the Mean Square Error (MSE) of the SSIDM is 2.172, which is 57.98% less than that of the conventional single-lane IDM. The SSIDM can accomplish stepless switching comparable to driver's behavior between the car-following behavior and the lane-changing behavior, with greater precision than IDM.

Reinforcement learning is used for air combat problems in recent years, and the idea of curriculum learning is often used for reinforcement learning, but traditional curriculum learning suffers from the problem of plasticity loss in neural networks. Plasticity loss is the difficulty of learning new knowledge after the network has converged. To this end, we propose a motivational curriculum learning distributed proximal policy optimization (MCLDPPO) algorithm, through which agents trained can significantly outperform the predictive game tree and mainstream reinforcement learning methods. The motivational curriculum learning is to help the agent gradually improve their combat ability by observing the agent's unsatisfactory performance and providing corresponding rewards as a guide. Additionally, a complete tactical maneuver is encapsulated based on existing air combat knowledge, and through the flexible use of these maneuvers, some tactics beyond human knowledge can be realized. In addition, we designed an interruption mechanism for the agent to increase the frequency of decision-making when the agent faces an emergency. When the number of threats the agent receives changes, the current action will be interrupted to reacquire observations and make decisions again. Using the interruption mechanism can significantly improve the ability of the agent. To simulate actual air combat better, we built an air combat environment based on digital twin technology to create an air combat engine core such as missiles and radars. Based on this environment, we develop a distributed intelligent training system that employs Redis as the cache and obtains the data generated in the distributed environment through a multi-threaded TCP/IP protocol, which significantly increases the training data throughput and helps the agent accelerates convergence. The experimental results demonstrate that the agent can fully exploit the situational information to make reasonable decisions and affords air combat tactical adaption, verifying the effectiveness of the algorithmic framework proposed in this paper.

Currently, the number of lightning casualties and casualty rates have significantly reduced in developed countries, but there has been no significant reduction in developing countries. On the one hand, this is due to the high frequency of lightning; on the other hand, the vulnerability of people in developing countries is also an influencing factor. Through case analysis and summary, this paper expounds on lightning injury’s mechanism and clinical manifestations. It points out that lightning injury is mainly related to heart problems and the impact on the nervous system, rather than burns, which usually cause fewer consequences. Medical treatment needs to pay attention to the order and principles of treatment. Implementing CPR and auxiliary AED is the most effective way to save lives. Attention should be paid to the practical and effective treatment and nursing of lightning stroke sequelae. Finally, combined with the situation of lightning casualties in china, the existing problems are put forward during the process of early treatment, post-hospital treatment, and nursing observation, which provides an objective basis for the cognition of the scientific nature of the lightning injury.

Collapsibility is an inherent characteristic of loess, which is often treated by adding industrial materials such as cement and lime in engineering, it seriously damages the reclamation performance of soil. Degradable calcium lignosulfonate (CLS) has a good prospect in balancing soil stabilization and environmental protection. Therefore, this paper evaluates the collapsibility and mechanical characteristics of CLS improved loess based on the collapsibility test, grey correlation analysis, and unconfined compressive strength test. The results show that when the content is 3%, the stabilization effect is most obvious, and the collapsibility coefficient can be reduced by more than 95%. The order of grey correlation degree of collapsibility on each index is moisture content, void ratio, dry density, and CLS content from large to small. The unconfined compressive strength increases rapidly in the first 14 days and then decreases with the content. When the content is too high, the strength of improved loess is lower than that of plain loess. Combined with SEM, microstructure parameters, and X-ray diffraction analysis, the carbonate minerals can play the role of filling pores and connecting soil particles, which reduces the grain size of mineral composition and the thickness of the electric double layer and makes the structure more compact. The research results have scientific significance and application value for the ecological modification research and engineering application of soil.

Controlling and understanding Cu-catalyzed homocoupling reaction is crucial to prompt the development of efficient Cu-catalyzed cross-coupling reactions. The presence of a coordinating base (hydroxide, methoxide) enables the B-to-Cu(II) transmetalation from aryl boronic acid to CuIICl2 in methanol, through formation of a mixed Cu-(μ-OH)-B intermediates. A second B-to-Cu transmetalation to form bis-aryl Cu(II) complexes is disfavored. Instead, organocopper(II) dimers undergo a coupled transmetalation-electron-transfer (TET) allowing the formation of a bis-organocopper(III) complexes readily promoting reductive elimination. Based on this mechanism some guidelines are suggested to control the undesired formation of homocoupling product in Cu-catalyzed cross-coupling reactions.

Various designs of spherical robots using barycenter offset mechanisms were previously reported. This kind of robots offers advantages such as turning in placeor moving in any direction at any time. Yet, the approaches resulting in a balanced robot, which could roll with reduced energy costs once accelerated, are scarce. We introduce anovel robot of this type. The feasibility of the approach is verified on a cylindrical robot. This paper presents an open-source, remotely controlled, robotic cylinder. The robot uses a specifically designed mechanism to displace a mass in its center, which causes the cylinder to roll forwards or backwards. The movement characteristics of the cylinder, as well as the mathematical and physical limitations of the mechanism were studied. An intuitive user interface allows the robot to be controlled through WiFi. This robot was manufactured only with readily available and inexpensive materials, which would make it a suitable platform for education, typically in the fields of physics and engineering.

In this paper, we propose an unsupervised blind restoration model for images in hybrid degradation scenes. The proposed model encodes the content information and degradation information of images and then uses the attention module to disentangle the two kinds of information. It can improve the ability of disentangled presentation learning for a generative adversarial network (GAN) to restore the images in hybrid degradation scenes, enhance the detailed features of restored image and remove the artifact combining the adversarial loss, cycle-consistency loss, and perception loss. The experimental results on the DIV2K dataset and medical images show that the proposed method outperforms existing unsupervised image restoration algorithms in terms of peak signal-to-noise ratio (PSNR), structural similarity (SSIM), and subjective visual evaluation.

Our bodies produce a host of electrophilic species that can label specific endogenous proteins in cells. The signaling roles of these molecules are underactive debate. However, in our opinion it is becoming increasingly likely that electrophiles can rewire cellular signaling processes at endogenous levels. Attention is turning more to understanding how nuanced electrophile signaling in cells is. In this perspective, we describe recent work from our laboratory that has started to inform on different levels of context-specific regulation of proteins by electrophiles. We discuss the relevance of these data to the field, and to the broader application of electrophile signaling to precision medicine development, beyond the traditional views of their pleiotropic cytotoxic roles.

Cooperative Non-Orthogonal Multiple Access (NOMA) with Simultaneous Wireless Information and Power Transfer (SWIPT) communication can effectively improve the spectrum efficiency and energy efficiency of the wireless networks with extend coverage. An important design issue is to incentivize a relaying center user to participate in the cooperative process and achieve a win-win situation to both the BS and the center user. Some private information of the center users are hidden from the BS in the networks. We apply a contract theory-based incentive mechanism under such asymmetric information scenario to incentives center user to join the cooperative communication to maximize the BS profit utility and to guarantee the center user’s expect payoff. A match theory-based Gale-Shapley algorithm is proposed to obtain the optimal strategy with low computation complexity. Simulation results indicated the network performance of our proposed cooperative transmission is much better than the conventional NOMA transmission and the benefit utility of the BS with the stable match strategy is nearly close to the complete channel state information multi-users scenario while the center users get the satisfied expect payoffs.

The multi-material design and the adaptability of a modern process chain require joining connections with specifically adjustable mechanical, thermal, chemical or electrical properties, whereby previous considerations have focused primarily on the mechanical properties. With clinching, the multitude of possible combinations of requirements, materials and component or joint geometry makes it impossible to determine these joint properties empirically. As a result of the established and empirically based procedure, no model exists to date that considers all questions of joinability, i.e. the materials (suitability for joining), the design (joining safety) and the production (joining possibility) and allows a calculation of the achievable properties. It is therefore necessary to describe the physical properties of the joint as a function of the three bonding mechanisms force closure, form closure and material closure in relation to the application. This approach enables the illustration of the relationships along the causal chain "joint requirement - binding mechanism - joining parameters". In this way the adaptability of the mechanical joining technology can be improved. A geometric comparison is made using metallographic cross sections, of clinched joints of the combination of aluminum and steel. The torsional testing of the rotationally symmetric clinching points for detection of the mechanical stress state are qualified as examination method and technological test. By measuring the electrical resistance in the base material, in the clinch joint and during the production cycle (after clinching, before precipitation hardening and after precipitation hardening), this change in the stress state can also be detected.

Based on 2010, 2013 and 2015 CGSS data, the impact of Internet use and social capital on the income gap among farmers in the past five years is assessed at three time points using the OLS method and a quantile regression method. The study finds that (1) the income gap among farmers increases continuously in the five-year period, while Internet use plays a positive impact on farmers’ income growth in all five quartiles; the coefficient differences are all significantly negative, indicating that Internet use plays a positive role in alleviating the income gap between high-income and low-income farmer subgroups, and (2) social capital plays a positive role in moderating the income gap among farmers and that Internet use by farmers expands the boundary of social capital, which in turn increases the income level of and alleviates the income gap among farmers.

Reconstructing ancestral species is a challenging endeavour: fossils are often scarce or enigmatic, and inferring ancestral characters based on novel molecular approaches (e.g. comparative genomics or developmental genetics) has long been controversial. A key philosophical challenge pertinent at present is the lack of a theoretical framework capable of evaluating inferences of homology made through integration of multiple kinds of evidence (e.g. molecular, developmental, or morphological). Here, I present just such a framework. I start with a brief history and critical assessment of attempts at inferring morphological homology through developmental genetics. I then bring attention to a recent model of homology, namely Character Identity Mechanisms (DiFrisco, Love, & Wagner, 2020), intended partly to elucidate the relationships between morphological characters, developmental genetics, and homology. I utilise and build on this model to construct the evaluative framework mentioned above, which judges the epistemic value of evidence of each kind in each particular case based on three proposed criteria: effectiveness, admissibility, and informativity, as well as providing a generalised guideline on how it can be scientifically operationalised. I then point out the evolution of the eumetazoan body plan as a case in point where the application of this framework can yield satisfactory results, both empirically and conceptually. I will conclude with a discussion on some potential implications for more general philosophy of biology and philosophy of science, especially surrounding evidential integration, models and explanation, and reductionism.

Background:Boom in nanotechnology in current era has sketched unforeseen transformations in number of fields, such as medicine, health care, food, space, agriculture, etc. The synthesis of nanoparticles with different chemical compositions, sizes, shapes and controlled disparities is an important area of research in this field. Over the last decade, the biosynthesis of metal nanoparticles has received considerable attention due to their unusual and fascinating properties, with various applications, over their bulk counterparts.Hypothesis: The nanoparticle can have huge application in the field of food, pharmaceutical, and cosmetic industries and thus become a major area of research. Green synthesis of zinc oxide nanoparticles (ZnO NPs) using plant extracts offers an eco-friendly and promising substitute to the conventional methods of chemical synthesis. Conclusion: In the arena of nanoparticle phytosynthesis, novel materials have been produced that are eco-friendly, cost-effective and stable. In the current situation, nanotechnology inspires progress in all spheres of life, and therefore the phytosynthetic path of nanoparticle synthesis has emerged as a safe and best alternative to conventional methods. This review summarizes the recent work in the field of zinc nanoparticle phytosynthesis and critically discusses the mechanism proposed behind it.

Over the last decade, there has been a growing interest in the use of a wide range of phytoadditives to counteract the harmful effects of heat stress in poultry. Willow (Salix spp.) is a tree with a long history. Among various forms, willow bark is an important natural source of salicin, β-O-glucoside of saligenin, but also of polyphenols (flavonoids and condensed tannins) with antioxidant, antimicrobial and anti-inflammatory activity. In light of this, the current review presents some literature data aiming to: (1) describe the relationship between heat stress and oxidative stress in broilers, (2) present or summarize literature data on the chemical composition of Salix species, (3) summarize the mechanisms of action of willow bark in heat-stressed broilers, (4) present different biological effects of the extract of Salix species in different experimental models.

In the present, the growth of digitization and worldwide communications make OCR systems of exotic languages a very important task. In this paper, we attempt to develop an OCR system for one of these exotic languages with a unique script, Amharic. Motivated by the recent success of the Attention mechanism in Neural Machine Translation (NMT), we extend the attention mechanism for Amharic text-image recognition. The proposed model consists of CNNs and attention embedded recurrent encoder-decoder networks that are integrated following the configuration of the seq2seq framework. The attention network parameters are trained in an end-to-end fashion and the context vector is injected, with the previously predicted output, at each time steps of decoding. Unlike the existing OCR model that minimizes the CTC objective function, the new model minimizes the categorical cross-entropy loss. The performance of the proposed attention-based model is evaluated against the test dataset from the ADOCR database which consists of both printed and synthetically generated Amharic text-line images and achieved promising results with a CER of 1.54% and 1.17% respectively.

Recently deep cross-modal hashing networks have received increasing interests due to its superior query efficiency and low storage cost. However, most of existing methods concentrate less on hash representations learning part, which means the semantic information of data cannot be fully used. Furthermore, they may neglect the high-ranking relevance and consistency of hash codes. To solve these problems, we propose a Self-Attention and Adversary Guided Hashing Network (SAAGHN). Specifically, it employs self-attention mechanism in hash representations learning part to extract rich semantic relevance information. Meanwhile, in order to keep invariability of hash codes, adversarial learning is adopted in the hash codes learning part. In addition, to generate higher-ranking hash codes and avoid local minima early, a new batch semi-hard cosine triplet loss and a cosine quantization loss are proposed. Extensive experiments on two benchmark datasets have shown that SAAGHN outperforms other baselines and achieves the state-of-the-art performance.

Corona virus disease 2019 (COVID-19) is caused by a Severe Acute Respiratory Syndrome-Coronavirus 2 (SARS-CoV-2), which is a positive strand RNA virus. The SARS-CoV-2 genome and its association to SAR-CoV-1 vary from ca. 66% to 96% depending on the type of betacoronavirdeae family members. With several drugs, viz. chloroquine, hydroxychloroquine, ivermectin, artemisinin, remdesivir, azithromycin considered for clinical trials, there has been an inherent need to find distinctive antiviral mechanisms of these drugs. Curcumin, a natural bioactive molecule has been shown to have a therapeutic potential for various diseases, but its effect on COVID-19 has not been explored. In this study, we show the binding potential of curcumin targeted to a variety of SARS-CoV-2 proteins, viz. spike glycoproteins (PDB ID: 6VYB), nucleocapsid phosphoprotein (PDB ID: 6VYO), membrane glycoprotein (PDB ID: 6M17) along with nsp10 (PDB ID: 6W4H) and RNA dependent RNA polymerase (PDB ID: 6M71) structures. Our results indicate that curcumin has high binding affinity towards nucleocapsid and nsp 10 proteins with potential antiviral activity.

I have recently reiterated that the cross-bridge is a calcium ATPase that is inhibited by magnesium and this arises because in normal hearts Myosin binding Protein-C prevents the use of MgATP as rate limiting substrate ensuring that Ca²⁺ replaces Mg²⁺ in the excitation pathway. Here I revisit the studies on [Ca²⁺] dependency of ATPase and tension under diastolic stretch with a different conclusion on Hill coefficients. This reveals the underlying mechanisms of the Frank-Starling Law and Hypertrophic myopathy are not the same, the former being kinase controlled.

Significance: Electrophile signaling is coming into focus as a bona fide cell signaling mechanism. The electrophilic regulation occurs typically through a sensing event (i.e., labeling of a protein) and a signaling event (the labeling event having an effect of the proteins activity, association, etc.). Recent advances: Herein, we focus on the first step of this process, electrophile sensing. Electrophile sensing is typically a deceptively simple reaction between the thiol of a protein-cysteine, of which there are around 200,000 in the human proteome, and a Michael acceptor, of which there are numerous flavors, including enals and enones. Recent data overall paint a picture that despite being a simple chemical reaction, electrophile sensing is a discerning process, showing labeling preferences that are often not in line with reactivity of the electrophile. Critical issues: With a view to trying to decide what brings about highly electrophile-reactive protein-cysteines, and how reactive these sensors may be, we discuss aspects of the thermodynamics and kinetics of covalent/non-covalent binding. Data made available by several laboratories indicate that it is likely that specific proteins exhibit highly stereo- and chemoselective electrophile sensing, which we take as good evidence for recognition between the electrophile and the protein prior to forming a covalent bond. Future directions: We propose experiments that could help us gain a better and more quantitative understanding of the mechanisms through which sensing comes about. We further extoll the importance of performing more detailed experiments on labeling and trying to standardize the way we assess protein-specific electrophile sensing.We propose experiments that could help us gain a better and more quantitative understanding of the mechanisms through which sensing comes about. We further extoll the importance of performing more detailed experiments on labeling and trying to standardize the way we assess protein-specific electrophile sensing.

Volatile organic compounds (VOCs) are among the most abundant air pollutants. Their high concentrations can adversely affect the human body and therefore, early detection of VOCs is of outmost importance. Among the different VOCs, in this review paper, we have focused our attention on the monitoring of acetaldehyde by chemiresistive gas sensors using nanostructured semiconducting metal oxides. These sensors not only can provide a high sensing signal for detection of acetaldehyde, but also high thermal and mechanical stability and low price. This review paper is divided into three major sections. First, we will introduce acetaldehyde as the target gas and the importance of its detection. Then, the fundamentals of chemiresistive gas sensors will be briefly presented and, in the last section, a survey of literature on acetaldehyde gas sensors will be discussed. Acetaldehyde sensors working mechanism, their structures and configurations are reviewed. Finally, the future development outlook and potential applications are discussed, giving a complete panoramic view for researcher working and interested in acetaldehyde detection for different purposes in many fundamentals and applicative fields.

The problem of Yukawa couplings being arbitrary parameters in the Standard Model Higgs mechanism is a long standing one due to their formulaic dependence on the Higgs Vacuum Expectation Value. We will attempt to solve this problem and provide a strong argument that the Yukawa couplings of charged leptons and down type quarks are not arbitrary parameters in the SM. A new methodology for predicting the Yukawa couplings will be presented by using Compton wavelengths, the Rydberg Constant and g-factors of charged leptons instead of relying on the Higgs VEV. We will then proceed to rewrite this new method in terms of an empirical formula that depends on the running of the fine-structure constant on the Q scale, charge and lepton quantum numbers and g-factors to predict the values of the Yukawa couplings for all three generations of charged leptons and d-type quarks. We will also touch on the subject of neutrinos both as Majorana and Dirac fermions respectively and make a prediction for the lightest possible Majorana neutrino and the differences between Dirac neutrinos and anti-neutrinos. We conclude that the Yukawa couplings are not arbitrary parameters in the SM and that this new formula provides very accurate results.

In order to study the crystallinity of different density polyethylenes, the experimental study on the transformation of the conductance mechanism under high electric field was carried out. The X-ray Diffraction(XRD), Different Scanning Calorimeter(DSC), Direct Current(DC) breakdown of Low-density polyethylene(LDPE), Linear low density polyethylene(LLDPE), Medium density polyethylene(MDPE) and High-density polyethylene(HDPE) and the electric field of 5-200kV/mm were tested. Conductivity characteristics experiments, in addition, using the mathematical formula of a variety of conductance mechanisms, the electric field-current density curves of the four kinds of polyethylene were fitted to analyze the conductance transition of the above four kinds of polyethylene in non-ohmic regions under different high field strengths. mechanism. The experimental results show that as the density of polyethylene increases, the crystallinity increases continuously, and the continuous increase of crystallinity causes the electric conduction flow under the same field strength to decrease significantly. The field strength corresponding to the two turning points in the conductance characteristic curve increases simultaneously. Large, the breakdown field strength increases; through analysis, it is found that in the high field, as the electric field increases, the conductance mechanism develops from the ohmic conductance of the low field strength region to the bulk effect of the high field strength region (Poole-Frenkel). Then the electrode effect to the high field strength (Schottky), and the threshold field strength of this conductance mechanism transition increases with the increase of crystallinity.

Photosynthetic function, photoprotection, and the response of related proteomics of mulberry (Morus alba L.) seedling leaves under NaCl and NaHCO3 stress with the same Na+ concentration (100 mmol•L-1) were studied by using photosynthetic gas exchange and chlorophyll fluorescence techniques combined with TMT proteomics. The results showed that NaCl stress had no significant effect on photosystem II (PSII) activity in mulberry seedling leaves, and the expressions of the related proteins, OEE3-1 and PPD4, of the PSII oxygen-evolving complex (OEC) and the antenna proteins, CP24 10A, CP26, and CP29, of LHCII in the leaves also increased to varying degrees. The photosystem I (PSI) activity in the leaves of mulberry seedling also increased, and the expressions of some proteins, PsaF, PsaG, PsaH, PsaL, PsaN, and Ycf4, in PSI increased significantly under NaCl stress. Under NaHCO3 stress, the activity of PSII and PSI and the expression of their protein complexes and the electron transfer-related proteins significantly decreased. NaCl stress had little effect on RuBP regeneration during dark reaction in the leaves and the expressions of glucose synthesis related proteins and net photosynthetic rate (Pn) did not decrease significantly. The leaves could adapt to NaCl stress by reducing stomatal conductance (Gs) to increase water use efficiency (WUE). Under NaHCO3 stress, the expression of dark reaction-related proteins was mostly down-regulated, and Gs was significantly reduced, which indicated that non-stomatal factors were important reasons for the significant inhibition of carbon assimilation. In the photoprotective mechanism under NaCl stress, the expression of cyclic electron flow (CEF) related proteins, ndhH, ndhI, ndhK, and ndhM, involved in NAD(P)H dehydrogenase (NDH) and the key enzyme of the xanthophyll cycle, violaxanthin de-epoxidase (VDE) were up-regulated. In addition, the ratio of xanthophyll cycle components (A+Z)/(V+A+Z) was increased. The expressions of proteins FTR and Fd-NiR, which are related to Fd-dependent ROS metabolism and nitrogen metabolism, were also significant up-regulated under NaCl stress, which can effectively reduce the electronic pressure on Fd. Under NaHCO3 stress, the expressions of CEF-related proteins, VDE, ZE, FTR, Fd-NiR, Fd-GOGAT, SGAT, and GGAT, were significant down-regulated, and the photoprotective mechanism, like the xanthophyll cycle, CEF, and photorespiration, might be damaged, resulting in the inhibition of PSII activity and carbon assimilation in leaves of mulberry seedling under NaHCO3 stress.

Systems biology has been established for more than a decade in the post-genomic era. With the help of the computational and mathematical tools, systems biology reconstitutes the entire scenario of the cell, tissue and even organism from the pieces data generated in the past decades. However, the modern biology is mainly focusing on the structure and function of the biomolecule, cell, tissue or organ, which are far from the essence of the life because of missing thermodynamic information. It is doubtable that the current systems biology-based omics is no-how to fully understand the dynamic courses of the structure, function and information in life. For this reason, we promote a novel concept of aquamoleculomics, in which the biological structure and function as well as thermodynamic characteristics and bioinformation of the aquamolecule complexes are included in this theoretical model of systems biology. Water is mother of life, matter and matrix of organism. Indeed, the fundamental roles of H₂O molecules in biological processes might be dramatically underestimated. Extremely speaking, H₂O networks in the living system might be engaged in all the biological processes including building all the biological structures, the residential places of the motherhood molecules as the honeycombs of honeybees.

To enhance the safety of power grid operations, this study proposes a high-precision short-term photovoltaic power prediction method that integrates information from surrounding pho-tovoltaic stations and the Conv-LSTM-ATT model. In the deep learning prediction model, not only is numerical weather prediction (NWP) data from the target photovoltaic station used as input features, but also highly correlated features from nearby photovoltaic stations are incor-porated. The research begins by analyzing the correlation between irradiance and power se-quences, along with distance factors, to calculate a composite similarity index between the target and other regional photovoltaic stations. Stations with high similarity indices are then selected as data sources. Subsequently, Bayesian optimization techniques are employed to find the optimal data fusion ratios. Ultimately, using the selected data, power prediction mod-eling is conducted via the Conv-LSTM-ATT deep neural network. Experimental results con-firm the superiority of the proposed model, which demonstrates higher predictive accuracy compared to three other classical models. The data fusion strategy determined by Bayesian optimization significantly enhances prediction accuracy, reducing the root mean square error (RMSE) of the test set by 20.04%, 28.24%, and 30.94% for three weather types, respectively.

The purpose of this study is to investigate the failure mechanism and preventive strengthening methods of prefabricated full length small box girder (PSBG) under car explosion. After damage analysis during blast loads using the commercial software Autodyn, three strengthening methods are presented to improve the blast mitigation performance. The results show that the failure modes and bearing capacity are significantly different with various strengthening measures. Adhering U-shaped steel plate can effectively enhance the shear performance of PSBG under blast loads. Strengthening the bottom of the upper flange of box girder with steel plate can effectively mitigate the local bending failure, and enhance the overall flexural capacity during car explosion.

This review provides a systematic analysis of the literature data on the electrodeposition of composite coatings using plating baths based on a new generation of room-temperature ionic liquids, known as deep eutectic solvents (DESs). Such systems offer several advantages over traditionally used aqueous electrolytes and organic solvent-based electrolytes. The colloidal-chemical properties of suspension and colloidal electrolytes for composite deposition are thoroughly examined. New theories describing the kinetics of co-deposition of composite layers are characterized. The kinetics and mechanism of electrochemical deposition processes of composite coatings with metallic matrices are discussed. Case studies regarding the electrodeposition of composite coatings based on electrodeposited copper, silver, zinc, tin, nickel, cobalt, and chromium from DES-assisted electroplating baths are described and systematized. The main prospective directions for further research in the discussed scientific area are highlighted.

This paper proposed a three-layer distributed simulation network architecture: 1. Distributed virtual simulation network, 2. Perception and control sub-network, and 3. Collaborative communication service network. This simulation architecture runs on a distributed platform. The platform can provide a unique virtual scenario and several simulation services to verify the individual robot system's basic perception, control, and planning algorithms and the distributed collaborative algorithms of heterogeneous multi-robot systems. Furthermore, we designed a simulation experiment scenario for classical heterogeneous robot systems such as unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs). At last, We gave a rough estimation model of the bandwidth.

Skin cancer is a prevalent type of malignancy on a global scale, and the early and accurate diag-nosis of this condition is of utmost importance for the survival of patients. The clinical assessment of cutaneous lesions is a crucial aspect of medical practice, although it encounters several obsta-cles, such as prolonged waiting time and misinterpretation. The intricate nature of skin lesions, coupled with variations in appearance and texture, presents substantial barriers to accurate clas-sification. As such, skilled clinicians often struggle to differentiate benign moles from early ma-lignant tumors in skin images. Although deep learning-based approaches such as convolution neural networks have made significant improvements, their stability and generalization continue to confront difficulties, and their performance in accurately delineating lesion borders, capturing refined spatial connections among features, and using contextual information for classification is suboptimal. To address these limitations, we propose a novel approach for skin lesion classification which combines snake models of Active Contour (AC) Segmentation, ResNet50 for feature ex-traction and a Capsule Network with a fusion of lightweight attention mechanisms, to attain the different feature channels and spatial regions within feature maps, enhance the feature discrimi-nation, and improve accuracy. We employed the Stochastic Gradient Descent (SGD) optimization algorithm to optimize the model's parameters. The proposed model is implemented on publicly available datasets, namely HAM10000 and ISIC 2020. The experimental results showed that the proposed model achieved an accuracy of 98% and AUC-ROC of 97.3%, showcasing substantial potential in terms of effective model generalization compared to existing state-of-the-art (SOTA) approaches. These results highlight the potential for our approach to reshape automated derma-tological diagnosis and provide a helpful tool for medical practitioners.

Obesity is a global health concern. Recent research has suggested that the development of anti-obesity ingredients and functional foods should focus on natural products without side effects. We investigated the anti-obesity efficacy and mechanisms of action of Brassica juncea extract (BJE) using in vitro and in vivo obesity models. In in vitro experiments, BJE treatment downregulated adipogenic-related proteins CCAAT/enhancer-binding protein-α (C/EBP-α), peroxisome proliferator-activated receptor-γ (PPAR-γ), adipocyte protein 2 (aP2), and lipid synthesis-related protein acetyl-CoA carboxylase (ACC). It also upregulated the heat generation protein peroxisome proliferator-activated receptor gamma coactivator-1α (PGC-1α) and fatty acid oxidation protein carnitine palmitoyltransferase-1 (CPT-1). Oral administration of BJE decreased body weight, alleviated liver damage, and inhibited lipid accumulation in high-fat diet (HFD)-induced obese mice. Inhibition of lipid accumulation by BJE in vivo was associated with decreased expression of adipogenic and lipid synthesis proteins and increased expression of heat generation and fatty acid oxidation proteins. BJE administration improved obesity by decreasing adipogenesis and activating heat generation and fatty acid oxidation in 3T3-L1 cells and in HFD-induced obese C57BL/6J mice. These findings indicate that BJE is a promising natural means of preventing obesity-related metabolic diseases.

Street view images can help us better understand the city environment and potential characteristics. With the development of computer vision and deep learning, the technology of semantic segmentation algorithms has become more mature. However, DeeplabV3+, which is commonly used in semantic segmentation, has shortcomings such as a large number of parameters, high requirements for computing resources, and easy loss of detailed information. Therefore, this paper proposes LM-DeeplabV3+, which aims to greatly reduce parameters and computations of the model while ensuring the segmentation accuracy. Firstly, the lightweight network MobileNetV2 is selected as the backbone network, and the ECA attention mechanism is introduced after MobileNetV2 extracts shallow features to improve the ability of feature representation; secondly, the ASPP module is improved, and on its basis, the EPSA attention mechanism is introduced to achieve cross-dimensional channel attention and important feature interaction; thirdly, a loss function named CL loss is designed to balance the training offset of multiple categories and better indicate the segmentation quality. This paper conducted experimental verification on the Cityspaces dataset, and the results showed that the mIoU reached 74.9%, which was an improvement of 3.56% compared to DeeplabV3+; the mPA reached 83.01%, which was an improvement of 2.53% compared to DeeplabV3+.

FV (finger vein) identification is a biometric identification technology that extracts the features of FV images for identity authentication. To address the limitations of CNN-based FV identification, particularly the challenge of small receptive fields and difficulty in capturing long-range dependencies, an FV identification method Let-Net(Large kernel and attention mechanism Network) was introduced, which combines local and global information. Firstly, Let-Net employs large kernels to broaden the receptive field and incorporates depthwise convolution with residual connections to reduce parameter count. Secondly, Let-Net integrates an attention mechanism to enhance the information flows in channels and spaces for more comprehensive and distinctive FV feature extraction. The experimental results on nine public datasets show that Let-Net has excellent identification performance, and the EER and accuracy rate on the FV_USM dataset can reach 0.04% and 99.77%. The parameter number and FLOPs of Let-Net are only 0.89M and 0.25G, which means that the time cost of training and reasoning of the model is low, and it is easier to deploy and integrate into various applications.

Shut-in after fracturing is generally adopted for wells in shale oil reservoirs, and imbibition occurring in matrix nanopores has been proven as an effective way to improve recovery. In this research, the molecular dynamics (MD) simulation was used to investigate the effects of wettability and pressure on nanopores imbibition during shut-in for a typical shale reservoir Jimsar. The results indicate that the microscopic advancement mechanism of the imbibition front is the competitive adsorption between “interfacial water molecules” at the imbibition front and “adsorbed oil molecules” on the pore wall. The essence of spontaneous imbibition involves the adsorption and aggregation of water molecules onto the hydroxyl groups on the pore wall. The flow characteristics of shale oil suggest that the overall push of the injected water to the oil phase is the main reason for the displacement of adsorbed oil molecules. Thus, shale oil especially the heavy hydrocarbon component in the adsorbed layer tends to slip on the walls. However, the weak slip ability of heavy components on the wall surface is an important reason that restricts the displacement efficiency of shale oil during spontaneous imbibition. The effectiveness of spontaneous imbibition is strongly dependent on the hydrophilicity of the matrix pore's wall. The better hydrophilicity of the matrix pore's wall facilitates higher levels of adsorption and accumulation of water molecules on the pore wall and requires less time for “interfacial water molecules” to compete with adsorbed oil molecules. During the forced imbibition process, the pressure difference acts on both the bulk oil and the boundary adsorption oil, but mainly on the bulk oil, which leads to the occurrence of wetting hysteresis. Meanwhile, shale oil still existing in the pore always maintains a good stratified adsorption structure. Because of the wetting hysteresis phenomenon, as the pressure difference increases, the imbibition effect gradually increases, but the actual capillary pressure gradually decreases and there is a loss in the imbibition velocity relative to the theoretical value. Simultaneously, the decline in hydrophilicity further weakens the synergistic effect of pressure difference because of the more pronounced wetting hysteresis. Thus, selecting an appropriate well pressure enables cost savings and maximizes the utilization of the formation's natural power for EOR.

Peanut leaf spot is a worldwide disease whose prevalence poses a major threat to peanut yield and quality, and accurate prediction models are urgently needed for timely disease management. In this study, we proposed a novel peanut leaf spot prediction method based on an improved long short-term memory (LSTM) model and multi-year meteorological data combined with disease survey records. Our method employed a combination of convolutional neural network (CNN) and LSTM to capture spatial-temporal patterns from the data and improve the model ability to recognize dynamic features of the disease. In addition, we introduced an attention mechanism module to enhance model performance by focusing on key features. Through several hyper-parameter optimization adjustments, we identified a peanut leaf spot disease condition index prediction model with a learning rate of 0.001, a number of cycles (Epochs) of 800, and an optimizer of Adma. The results showed that the integrated model demonstrated excellent prediction ability, obtaining an RMSE of 0.063 and an R2 of 0.951, which reduced the RMSE by 0.253 and 0.204, and raised the R2 by 0.155 and 0.122, respectively, compared to the single CNN and LSTM. Predicting the incidence and severity of peanut leaf spot disease based on the meteorological conditions and neural networks is feasible and valuable to help growers made accurate management decisions and reduced disease impacts through optimal fungicide application timing.

Due to the particular structure of the beveloid gear, it can’t be hobbed directly by an ordinary gear hobbing machine. The existing processing method is complex and high-cost. Therefore, the mass production and industrialization of beveloid gears are limited. To improve the machining efficiency and accuracy of processing beveloid gears, we proposed a hobbing method via the modification of ordinary hobbing machines. At first, we completed the derivation and calculation of the relevant processing parameters of the beveloid gear based on the study of the structural characteristics of the beveloid gear and the principle of hobbing machining. Then, we proposed and designed a beveloid gear hobbing method, and the modification of the ordinary hobbing machine was completed by using a hanging wheel mechanism in synchronous belt type. Finally, we completed the actual hobbing of the beveloid gear, and the feasibility of the proposed method was verified. After that, we analyzed the machining error of the trial-produced beveloid gear, the results showed that the accuracy of the trial-produced beveloid gear met the 6-level standard, which also verified the accuracy of the proposed method.

Raman scattering has been employed to study in detail the concentration dependence of the vibrational modes for the hexamethylenetetramine (HMTA) aqueous solutions. The formation of protonated and/or aggregated species has been clarified by comparing the experimental with the theoretically predicted vibrational spectra by means of quantum mechanical calculations. The analysis has shown that the vibrational modes of the solutions arise from a contribution of the vibrational modes of the HMTA self-aggregates and hetero-aggregates of HMTA with water molecules that are formed in the low- and intermediate-concentration region, respectively. The protonation of HMTA is ruled out due to the large differences between the experimental and the theoretically calculated spectra of the protonated molecules of HTMA in the fingerprint region. In the low-concentration solutions, the hetero-aggregation reaction of HMTA with water is the dominant mechanism, while at higher concentrations a self-aggregation mechanism occurs. Ultrasonic absorption and velocity measurements were carried out for hexamethylenetetramine aqueous solutions. The acoustic spectra reveal the presence of only one single Debye-type relaxation process that is assigned to the aggregation mechanism of HMTA. The sound absorption data follow two different dependencies on HMTA mole fraction. The crossover 0.018 mole fraction signifies two separate regions with distinct structural characteristics. The relaxation mechanism observed in dilute solutions is attributed to hetero-association of HMTA with water molecules, while at higher concentrations the observed relaxation process is assigned to the self-association reaction of HMTA molecules. This structural transformation is also reflected in several physicochemical properties of the system, including the kinematic viscosity, the mass density, the sound speed, and the adiabatic compressibility of the HMTA aqueous solutions. The combination of vibrational and acoustic spectroscopies with molecular orbital calculations allowed us to disentangle the underlying processes and to elucidate the observed relaxation mechanism in the HMTA aqueous solutions.

. Manufacturers are increasingly adopting mixed-flow manufacturing models to meet the growing customized, diverse, and dynamic customer demand. In such an environment, material distribution scheduling optimization is vital for smooth operations and is integral to production management. However, manufacturers frequently encounter problems like disordered and delayed material distribution. Traditional scheduling methods suffer from problems like inadequate transparency, delayed decision directives, and suboptimal results, impacting performance. To this end, this study proposes a dynamic material distribution scheduling optimization model and strategy based on digital twin (DT) to address these problems. Firstly, we introduce workstation satisfaction and establish a material distribution path optimization model minimizing total distribution cost while maximizing workstation satisfaction. Subsequently, we present a cloud-edge computing-based decision framework and explain the DT-based material distribution system's components and operation. Furthermore, a dynamic material distribution scheduling optimization mechanism based on DT is designed. By incorporating a savings method and incentive, penalty strategies, improvements are made to the path node selection probabilities and the information pheromone update rules of the traditional ant colony optimization (ACO) algorithm. Finally, a numerical case study, using real data from collaborating enterprises, validates the proposed algorithm and strategy. This research offers valuable insights into logistics management and algorithm design in smart manufacturing environments.

To address the deficiency of existing relation extraction models in effectively extracting relational triplets pertaining to railway traffic knowledge in Tibet, this paper constructs a Tibet Railway Traffic text dataset and provides an enhanced relation extraction model. The proposed model incorporates subject feature enhancement and relational attention mechanisms. It leverages a pre-trained model as the embedding layer to obtain vector representations of text. Subsequently, the subject is extracted and its semantic information is augmented using an LSTM neural network. Furthermore, during object extraction, the multi-head attention mechanism enables the model to prioritize relations associated with the aforementioned features. Finally, objects are extracted based on the subjects and relations. The proposed method has been comprehensively evaluated on multiple datasets, including the Tibet Railway Traffic text dataset and two public datasets. The results on the Tibet dataset achieves an F1-score of 93.3\%, surpassing the baseline model CasRel by 0.8\%, indicating a superior applicability of the proposed model. On the other hand, the model achieves F1-scores of 91.1\% and 92.6\% on two public datasets, NYT and WebNLG, respectively, outperforming the baseline CasRel by 1.5\% and 0.8\%, which highlights the good generalization ability of the proposed model.

Understanding the thermal cracks of rock caused by high temperature is of great help to the development of underground engineering, such as geothermal mining, underground coal gasification. Although there has been many study on thermal cracking, it is not systematic and in-depth enough. In order to deeply study the thermal crack mechanism of rock, this paper conducted thermal cracking experiments on granite at different temperatures and heating/cooling paths, and qualitative and quantitative analysis was conducted on the crack initiation characteristics, propagation paths, and crack network morphology of rock thermal crack under different test conditions. The thermal crack mechanism was also analyzed from the perspectives of mineral petrology, fracture mechanics, thermodynamics, and other aspects. The research results show that there are two obvious mutation points in the study temperature range for samples with fast cooling paths (SF path: slow heating and fast cooling; FF path: fast heating and fast cooling), around 200-300 ℃ and 600 ℃, respectively, while for samples with slow cooling paths (SS path: slow heating and slow cooling; FS path: fast heating and slow cooling), there is only one mutation point around 600 ℃. The initiation positions of thermal cracking under all temperature paths are relatively similar, with intergranular crack located between particles at the edge of the sample or intercrystalline crack in the middle of feldspar or quartz aggregates. The initiation temperature of SF and FF path specimens is relatively low compared to SS and FS path specimens, and the number and size of cracks is small. The crack network structure formed by the SF path is the most complex, with the largest crack ratio and cumulative crack length; The crack network structure formed by the FF path is relatively complex, with a larger main crack size but relatively fewer secondary cracks; The FS and SS paths do not form a complex network with good connectivity. The process of thermal crack development can be divided into three stages: the development of small cracks, the joint development of main cracks and small cracks, and the connection of cracks into a network structure. The mechanism of thermal crack propagation is that the expansion and thermal conductivity between different crystals are different. The thermal stress caused by temperature gradient and the tension or shear stress caused by the inconsistent deformation of crystals form stress concentration in weak areas such as particles boundary, cleavage, and original cracks. Firstly, it causes some crystals with smaller strength or less rounded shape to crack, and when the combined stress is large, the cracks will gradually expand along the existing fine cracks. This also explains that the most main cracks of the SF and FF path specimens mainly surround some large mineral aggregates or between particles.

With the rapid development in Beijing, there is a critical need to explore the circumstance and reveal the mechanisms of precious urban natural resources. In this context, urban blue space has attracted more and more attention by driving microcirculation, cooling heat islands, and relaxing residential. We extracted the UBS at Beijing using remote sensing, explored the spatial and temporal development in the last two decades via USDA methods, uncovered the full spectrum of landscape patterns from an ecological perspective, and simulated the mechanisms of the UBS area and the landscape quantitatively. We found that: (1) The UBS area in Beijing increased with fluctuation from 2000 to 2020. (2) The spatial clustering has distributed stable with some subtle changes. (3)The ecological circumstance has improved in the last 21 years in Beijing, with the increasing habitat diversity and richness, while the inferior landscape fragmentation has indicated some severe challenges. (4) Natural factors impact urban blue space areas more than social ones, while both similarly influence the UBS landscape. (5) Vegetation circumstances and precipitation are the most important natural factors on both area and landscape of UBS, and population and artificial surface are the most important social factors.

In recent times, the soft robotics field is gaining numerous research focus owing to its high level of manipulation capabilities unlike traditional rigid robots, which gives room for an increasing use in other areas. However, compared to traditional rigid gripper robots, being capable of controlling/obtaining overall body stiffness when required is yet to be further explored since soft gripper robots have inherently less rigid properties. unlike previous designs with very complex variable stiffness systems, this paper demonstrates a soft gripper design with minimum system complexity while being capable of varying the stiffness of a continuum soft robotic actuator and proves to have potential applications in gripping objects of various shapes, weights & sizes. The soft gripper actuator comprises two separate mechanisms; the pneumatic mechanism for bending control and the mechanical structure for stiffness variation by pulling tendons using stepper motors which compresses the actuator, thereby changing the overall stiffness. The pneumatic mechanism was first fabricated and then embedded into another silicon layer during which it was as well merged with the mechanical structure for stiffness control. By first pneumatically actuating the actuator which causes bending and then pulling the tendons, we found out that the actuator stiffness value can be increased up to 145 % its initial value, and the gripper can grasp & lift a weight of up to 2.075 kg.

In view of the Practical Byzantine Fault Tolerance (PBFT) consensus algorithm all nodes participate in the consensus, the three-stage process has problems such as large communication overhead, random selection of master nodes and lack of reward and punishment mechanism. A Speculative Practical Byzantine Fault Tolerance (SP-PBFT) is proposed. Firstly, the consensus protocol was optimized, and a timeout mechanism was proposed to divide the consensus process into optimistic mode and pessimistic mode, which reduced the communication overhead under the premise of resisting Byzantine node attacks .Secondly, a node evaluation mechanism was proposed to calculate the node reputation value according to the node's historical behavior and give the corresponding reward or punishment, which reduced the possibility of malicious nodes participating in the consensus process. Finally, the Fibonacci grouping mechanism was used to reduce the number of nodes participating in the consensus process, fundamentally improving the consensus efficiency, avoiding the problem of centralization of the consensus process caused by the cumulative reputation value of nodes, and improving the enthusiasm of consensus nodes. Simulation experiments using Docker containers to simulate multiple nodes show that the SP-PBFT consensus algorithm proposed in this paper has better performance than PBFT consensus algorithm and other improved algorithms in terms of consensus delay, throughput, fault tolerance and communication complexity.

Remote sensing imagery is of great significance for policy decisions, especially for disaster assessment and disaster relief. To ensure the privacy and inviolability of personal buildings, the information containing these buildings must be anonymized during the remote sensing mapping process. Traditional processing methods for these targets in remote sensing mapping are mainly based on manual retrieval and image editing tools, which are inefficient. Deep learning provides a new direction for target hiding. Although the image inpainting method based on deep learning is faster than the manual method, the cost of training calculation is a disadvantage. And the element-wise product operation used in the model increases the risk of vanished or exploded gradients. We propose a Residual Attention Target Hiding (RATH) model for remote sensing target hiding based on deep learning. RATH uses residual attention modules to replace gated convolutions, reducing parameters and mitigating gradient issues. The residual attention module preserves gated convolution performance but provides an adjustable kernel size. RATH retains gated convolutions for dynamic feature selection and balances model depth and width. Furthermore, this paper modifies the contextual attention layer by adjusting the fusion process to enlarge the fusion patch size. Finally, we extend the edge-guided function to preserve the original target information and confound viewers. Ablation studies on an open dataset prove RATH’s efficiency for image inpainting and target hiding. RATH achieves state-of-the-art results with lower complexity. And it has the highest similarity for edge-guided target hiding. RATH enables robust, efficient target hiding for privacy protection in remote sensing imagery while balancing performance and complexity. Experiments show RATH's superiority over existing methods in hiding arbitrary-shaped targets.

The ozonation reaction in a bubble column reactor (BCR) has been widely used in the removal of phenol from wastewater, but the phenol removal efficiency in this type of reactor is limited because of low ozone solubility and reactivity in the system. In the present study, the phenol degradation was enhanced using α-Al2O3 as a packing material and a ZnO nanocatalyst in the BCR. The reactor diameter and height were 8 cm and 180 cm, respectively. The gas distributor was designed to include 52 holes of 0.5-mm diameter. Also, the gas holdup, pressure drop, and bubble size were measured as a function of the superficial gas velocity (i.e., 0.5, 1, 1.5, 2, 2.5, and 3 cm/s). The evaluation of the hydrodynamic parameters provided a deep understanding of the ozonation process to select the optimal operating parameters in the reactor. It was found that the best superficial gas velocity was 2.5 cm/s. A complete (100%) phenol removal was achieved for phenol concentrations of 15, 20, and 25 ppm at reaction times of 80, 90, and 100 min, respectively, using α-Al2O3 packing material and a ZnO nanocatalyst in the BCR. Additionally, the results provided a clear reaction mechanism describing the ozonized BCR. Finally, the applied treatment method can be used efficiently to remove phenol from wastewater at a low cost, with little consumed energy, and a simple operation.

Target recognition mainly includes three approaches: optical image-based, echo detection-based, and passive signal analysis-based methods. Among them, the passive signal-based method is closely integrated with practical applications due to its strong environmental adaptability. Based on passive radar signal analysis, we design an "end-to-end" model that cascades a noise estimation network with a recognition network to identify working modes in noise environment. The noise estimation network is implemented based on U-Net, which adopts a method of feature extraction and reconstruction to adaptively estimate the noise mapping level of the sample, which can help the recognition network to reduce noise interference. Focusing on the characteristics of radar signal, the recognition network is realized based on Multi-Scale Convolutional Attention Network (MSCANet). Firstly, the deep group convolution is used to isolate the channel interaction in the shallow network. Then, through the multi-scale convolution module, finer-grained features of the signal are extracted without increasing the complexity of the model. Finally, the self-attention mechanism is used to suppress the influence of low-correlation and negative-correlation channels and spaces. This method overcomes the problem that the conventional method is seriously disturbed by noise. We validated the proposed method in 81 kinds of noise environments, achieving an average accuracy of 94.65%. Additionally, we discussed the performance of six machine learning algorithms and four deep learning algorithms. Compared to these methods, proposed MSCANet achieved an accuracy improvement of approximately 17%. Our method demonstrates better generalization and robustness.

In order to effectively utilize red mud and reduce its occupation of land resources as well as its impact on the environment, experiments were conducted to develop stabilized soil materials using nano-SiO2 synergistically modified red mud and to investigate the curing mechanism of stabilized soil. The unconfined compressive strength, microscopic morphology and curing mechanism of the red mud-based stabilized soil materials with different amounts of modified materials were investigated. The test results show that after 7-days curing, the unconfined compressive strength of red mud-based stabilized soil meets the compressive strength requirement of road base material when nano-SiO2, gypsum and cement are synergistically modified. In such case, the soil structure has the lowest fracture rate and the best structural compactness when the amount of nano-SiO2 is 1%; It is found that the needle-like and columnar calcium alumina in the modified red mud-based stabilized soil increases, and the binding energy of hydration product ions in the modified material is improved; The chemical curing mechanism of modified red mud-based stabilized soil includes hydration reaction, volcanic ash reaction, promotion effect of nano-SiO2, and enhancement effect of gypsum. On this base, a model of early start hydration process of red mud-based stabilized soil promoted by nano-SiO2 is established.

Respiratory syncytial virus (RSV) RNA synthesis takes place in cytoplasmic viral factories also called inclusion bodies (IBs), which are membrane-less organelles concentrating the viral RNA polymerase complex. IBs assembly is driven by liquid-liquid phase separation promoted by interactions between the viral nucleoprotein N and the phosphoprotein P. We recently demonstrated that cyclopamine (CPM) inhibits RSV multiplication by disorganizing and hardening IBs. Although a single mutation in the viral transcription factor M2-1 induced resistance to CPM, the mechanism of action of CPM still remains to be characterized. Here, using FRAP experiments on reconstituted pseudo-IBs both in cellula and in vitro, we first demonstrated that CPM activity depends on the presence of M2-1 together with N and P. We show that CPM impairs the competition between P and RNA binding to M2-1. As mutations on both P and M2-1 induced resistance against CPM activity, we suggest that CPM may affect the dynamics of the M2-1−P interaction, thereby affecting the relative mobility of proteins contained in RSV IBs. Overall, our results reveal that stabilizing viral protein-protein interactions is an attractive new antiviral approach. They pave the way for the rational chemical optimization of new specific anti-RSV molecules.

The development of high-performance sensing materials for detecting or removing SF₆ decomposition gases is crucial for gas-insulated switchgear (GIS). In this work, the adsorption characteristics of the pristine porphyrin (Pr) and Fe-doped porphyrin (FePr) monolayers towards SF₆ decomposition gases were investigated using the first-principles calculations. Additionally, the electronic properties and sensing-mechanism were also examined. The findings indicate that both Pr and FePr monolayers exhibit thermodynamic stability. The intrinsic Pr monolayer only exhibits a moderate affinity towards the SO₂ molecule, however, its poor sensitivity of the Pr monolayer renders it unsuitable as the sensing-material. In contrast, the FePr monolayer exhibits favorable adsorption strength towards all five toxic gases (H₂S, SO₂, SOF₂, SO₂F₂, HF). The FePr monolayer exhibits chemisorption towards SO₂/SOF₂ gases, Furthermore, the microscopic mechanism of gases-substrate interaction is elucidated through the analysis of charge density difference, charge transfer, and density of states. Moreover, the FePr has excellent sensitivity for H₂S, SO₂, SO₂F₂, SOF₂ and HF molecules owing to the significant variations of the band gap, electrical conductivity and work function. In addition, the τ of H₂S, SO₂, and SOF₂ is 12.6 μs, 18.5 s and 15.4 s at 298 K, respectively. Our calculated results can offer theoretical guidance for the practical application of FePr-based sensing materials to detect SF6 decompositions gases.

With an increase in energy consumption globally, Fischer-Tropsch (FT) synthesis is a good alternative for producing fuels and chemicals from coal, natural gas or biomass. Among them, coal to liquids has been put into production in countries that have large coal reserves. In this process, Fe-based catalysts are commonly used due to their earth abundance, comparatively wide operation range and ready availability to handle low H2/CO ratio from coal. Despite their extensive applications, the kinetic and mechanistic understandings of Fe carburization and FT reaction on Fe-carbides are relatively limited due to the complexity of phase composition of the applied catalysts. This review summarizes the current state of knowledge of FT synthesis on Fe-carbide with an emphasis on underlying mechanism. Specifically, the employment of model catalyst, such as Raney-Fe, could provide a convenient way to furnish kinetic information regarding Fe carburization and subsequent FT reaction. A major challenge for further understanding catalytic reactions occurring at the Fe-carbide surface is correlating FT activity and selectivity to specific active site. To address this issue, the advancements of both DFT calculations and surface science techniques are highly demanded.

Fine-grained image classification remains an ongoing challenge in the computer vision field, which is particularly intended to identify objects within sub-categories. It is a difficult task since there is a minimal and substantial intra-class variance. The current methods address the issue by first locating selective regions with Region Proposal Networks (RPN), object localization, or part localization, followed by implementing a CNN Network or SVM classifier to those selective regions. This approach, however, makes the process simple by implementing a single-stage end-to-end feature encoding with a localization method, which leads to improved feature representations of individual tokens/regions by integrating the transformer encoder blocks into the Yolov5 backbone structure. These Transformer Encoder Blocks, with their self-attention mechanism, effectively captured the global dependencies and enabled the model to learn relationships between distant regions. This improved the model ability to understand context and captured long-range spatial relationships in the image. We also replaced the Yolov5 detection heads with three transformer heads at the output for object recognition using the discriminative and informative features maps from transformer encoder blocks. We established the potential of the single stage detector for the fine-grained image recognition task, by achieving state of the art 93.4% accuracy, as well as outperforming the existing Yolov5 model. The effectiveness of our approach is assessed using the Stanford car dataset, which includes 16,185 images of 196 different classes of vehicles with significantly identical visual appearances.

Forest fires are one of the world's deadliest natural disasters. Early detection of forest fires can help minimize the damage to ecosystems and forest life. In this paper, we propose an improved fire detection method YOLOv5-IFFDM for YOLOv5. Firstly, the fire and smoke detection accuracy and the network perception accuracy of small targets are improved by adding attention mechanism in the backbone network. Secondly, the loss function is improved and the SoftPool pyramid pooling structure is used to improve the regression accuracy and detection effect of the model and the robustness of the model. In addition, random Mosaic augmentation technique is used to enhance the data to increase the generalization ability of the model, and re-clustering of flame and smoke detection a priori frames are used to improve the accuracy and speed. Finally, the parameters of the convolutional and normalization layers of the trained model are homogeneously merged to further reduce the model responsibility to improve the detection speed. Experimental results on homemade forest fire and smoke datasets show that this algorithm has high detection accuracy and fast detection speed, with average accuracy of fire up to 90.5% and smoke up to 84.3%, and detection speed up to 75 FPS (frames per second transmission), which can meet the requirements of real-time and efficient fire detection.

Citation: To be added by editorial staff during production.

The successive steps of the oxidation mechanism of crocin, major compound of saffron, by the free OH• radical are investigated by the pulse radiolysis, steady-state (gamma) radiolysis methods and molecular simulations. The optical absorption properties of the transient species and their reaction rate constants are determined. The absorption spectrum of the oxidized radical of crocin resulting from the H-abstraction presents a maximum at 678 nm and a band at 441 nm, almost as intense as that of crocin. The spectrum of the covalent dimer of this radical contains an intense band at 441 nm and a weaker one at 330 nm. The final oxidized crocin, issued from radical disproportionation, absorbs weaker with a maximum at 330 nm. The molecular simulation results suggest that the OH• radical is electrostatically attracted by the terminal sugar and is scavenged predominantly by the neighbor methyl site of the polyene chain as in a sugar-driven mechanism. Based on detailed experimental and theoretical investigations, the antioxidant properties of crocin are highlighted.