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Pyriproxyfen (PPF) has been shown to affect the pupal stage and ecdysone levels in holometabolous insects, such as silkworms and mealworms. It remains unknown whether it affects hemimetabolous insects with their hormone levels in insects lacking a pupal stage. In this laboratory study, bioassays were conducted to investigate the effects of varying doses of PPF on Aphis craccivoraKoch (Hemiptera: Aphididae). Ultraperformance liquid chromatography–tandem mass spectrometry (UPLC–MS/MS) was used to determine the types and titers of juvenile hormone (JH) and 20-hydroxyecdysone (20E). Additionally, the effects of PPF on A. craccivorareproduction and molting, as well as its influence on relevant gene expression, were examined. The results revealed LC50and LC90values of 3.84 and 7.49 mg/l for PPF, respectively, after 48 h of exposure. The results demonstrated a significant reduction in the titer of JH III and a significant increase in the titer of 20E following treatment with PPF. However, there was no significant decrease observed in the titer of JH III skipped bisepoxide (JH SB3). A sublethal concentration of PPF was found to inhibit Krüppel homolog 1 (kr-h1) gene expression and reduce aphid reproduction, but it did not significantly impact ecdysone receptor expression and aphid molting. The results of this study demonstrate that PPF exhibits a lethal effect on aphids, thereby providing an effective means of control. Additionally, sublethal concentrations of PPF have been found to inhibit the JH in aphids, resulting in a decline in their reproductive ability and achieving the desired control objectives.

Data‐driven deep learning technology has a strong non‐linear mapping ability and has good development potential in geophysical inversion problems. Traditional inversion techniques offer broad generality, but they can remain trapped in local minima, particularly for three‐dimensional tunnelling resistivity inversion. In this work, we present an inversion methodology that combines traditional physics‐driven and deep learning data‐driven inversion approaches. To further support deep neural networks' dependability on unseen data, the interpretability of their working mechanism is explored. We execute migration learning based on small sample data after identifying the critical parameters that restrict the effectiveness of inversion by analysing the feature maps of various model data. We demonstrate, using both synthetic examples and field data, that the proposed method can improve the accuracy in detecting water‐bearing anomalies (caves and faults), which are typically encountered during tunnel excavation.

Juvenile hormone III (JH III) is a crucial hormone synthesized exclusively as R-stereoisomer in most insects. Herein, we established a mature Tris-HCl culture system for essential biochemical reactions and applied stable instrumental detection methods to analyze JH III, methyl farnesoate (MF) and juvenile hormone acid (JHA) using UPLC-MS/MS. Our results revealed that the R-JH III terminal synthesis pathway in Apis melliferafollows the “esterify then epoxidize” sequence, with precise methyl-(2E,6E)-farnesoate titer regulation and its spatial cis–transisomerism, achieving selective R-JH III synthesis. Furthermore, we observed that the preferred generation of S/R-JH III chiral enantiomers varied depending on the spatial cis–transisomerism of different MFs. Our results suggest that S-JH III could theoretically exist in insects, offering a novel perspective for understanding the synthesis mechanism of diverse complex juvenile hormones in different insect species.

The direct-current (dc) resistivity method is a commonly used geophysical technique for surveying adverse geological conditions. The resistivity model can be reconstructed from data by inversion, which is an important step in geophysical surveys. However, the inversion problem is a serious one that can easily lead to incorrect results. Deep learning (DL) provides new avenues for solving inverse problems, and these methods have been widely studied. Currently, most DL inversion methods for resistivity are purely data-driven and depend heavily on labels (real resistivity models). However, real resistivity models are difficult to obtain through field surveys. As an inversion network may not be effectively trained without labels, we built an unsupervised learning resistivity inversion scheme based on the physical law of electric field propagation. First, a forward modeling process was embedded into the network training to convert the predicted resistivity model to predicted data, and form a data misfit with the observation data. Unsupervised training independent of labels was realized using the data misfit as a loss function. Moreover, a dynamic smoothing constraint was imposed on the loss function to alleviate the ill-posed inverse problem. Finally, a transfer learning scheme was employed to adapt the network trained with simulated data to field data. Numerical simulations and field tests showed that the proposed method can accurately locate and depict geological targets.

Drought stress severely limits growth and causes losses in the yield of tea plants. Exogenous application of 24-epibrassinolide (EBR) positively regulates drought responses in various plants. However, whether EBR could contribute to drought resistance in tea plants and the underlying mechanisms has not been investigated. Here, we found that EBR application is beneficial for the drought tolerance of tea plants. The transcriptome results revealed that EBR could contribute to tea plant drought resistance by promoting galactinol and abscisic acid (ABA) biosynthesis gene expression. The content of galactinol was elevated by EBR and EBR-responsive CsDof1.1 positively regulated the expression of the galactinol synthase genes CsGolS2-1and CsGolS2-2to contribute to the accumulation of galactinol by directly binding to their promoters. Moreover, exogenous EBR was found to elevate the expression of genes related to ABA signal transduction and stomatal closure regulation, which resulted in the promotion of stomatal closure. In addition, EBR-responsive CsMYC2-2 is involved in ABA accumulation by binding to the promoters CsNCED1and CsNCED2to activate their expression. In summary, findings in this study provide knowledge into the transcriptional regulatory mechanism of EBR-induced drought resistance in tea plants.

Quasi-free-standing monolayer graphene (QFMLG) formed by Gd intercalation hosts considerable electronic density of states compared with regular epitaxial monolayer graphene (EMLG) on the SiC(0001) substrate. Here, we revealed that Gd-intercalated QFMLG with heavy electron doping exhibited a stronger interface adsorption energy than that of EMLG, which is beneficial for the growth of quasi-monolayer SnSe2films. Combining the in situ reflection high-energy electron diffraction, scanning tunneling microscopy, and X-ray photoelectron spectroscopy, we systematically investigated the morphology and chemical bonding states of the monolayer SnSe2films grown on the Gd-intercalated QFMLG substrate (SnSe2/QFMLG). We found that the SnSe2/QFMLG presents a quasi-layered growth mode with less bilayer islands formed; in contrast, the SnSe2grown on the EMLG substrate (SnSe2/EMLG) presents an island growth mode with a mixture of different thicknesses. Further angle-resolved photoelectron spectroscopic measurements allow us to observe that the monolayer SnSe2films on Gd-intercalated QFMLG exhibit an indirect band gap of ∼1.47 eV due to the pronounced charge transfer at SnSe2/QFMLG interfaces. In addition, we extracted the effective mass of holes located at the valence band maximum. Our results provide an effective way to improve the controlling of thickness in van der Waals growth of monolayer SnSe2and significant information in understanding the fundamental physical properties of monolayer SnSe2as a 2D semiconductor.

For aerobic static composting, fresh cow, pig, and chicken manures were used as feedstock and mixed with 10 % corn straws, which was considered as the bulking agent. In the composting process of different livestock and poultry manures, the changing trends of temperature, pH, conductivity, density, and other parameters were intensively studied. The results were as follows: (1) after the tail biogases of composting systems - using cattle manure, pig manure, and chicken manure - were introduced into the biofilter, the concentration of O2decreased slightly, but the concentration of CO2increased. The odour in these tail biogases declined significantly, and thus the biodegradation of tail biogas was obvious. (2) The oxygen consumption in the different periods of the composting process of these three manures was almost the same, and the average oxygen consumption for the three manures was 0.928, 0.937, and 0.945 m3/kg, respectively. Under standard conditions, the density of oxygen is 1.429 g/L, and the average oxygen consumption in the composting processes of these three manures was 1.326, 1.338, and 1.350 kg/kg, respectively.

The scattering process induced by impurities in graphene plays a key role in transport properties. Especially, the disorder impurities can drive the ordered state with a hexagonal superlattice on graphene by electron-mediated interaction at a transition temperature. Using angle-resolved photoemission spectroscopy (ARPES), we reveal that the epitaxial monolayer and bilayer graphene with various impurities display global elastic intervalley scattering and quantum interference below the critical temperature (34 K), which leads to a set of new folded Dirac cones at the Brillouin-zone center by mixing two inequivalent Dirac cones. The Dirac electrons generated from intervalley scattering without chirality can be due to the breaking of the sublattice symmetry. In addition, the temperature-dependent ARPES measurements indicate the thermal damping of quantum interference patterns from Dirac electron scattering on impurities. Our results demonstrate that the electron scattering and interference induced by impurities can completely modulate the Dirac bands of graphene.

REB2C2(RE = Y and lanthanides) compounds have gained attention for their unique layered crystal structure. However, there have been few reports about Raman spectroscopy of REB2C2compounds up to now. Here, the Raman spectrum of YbB2C2is obtained by a micro-Raman spectroscope and the first-principles calculations. Raman active vibrational modes of YbB2C2are confirmed as A1g(627 and 1311 cm−1), B1g(944 and 1172 cm−1), B2g(330 and 885 cm−1) and Eg(357 and 530 cm−1). Atomic displacements of these modes are different, they can be divided into two groups: A1g, B1gand B2gcorrespond to ring breathing (δin, in the plane) of B2C2layer; Egis due to ring deformation (δoop, out of the plane) of B2C2layer. These results are helpful to understand the individual structure of REB2C2.

The surface Ga content for a CIGSe absorber was closely related to variation in the open-circuit voltage (VOC), while it was generally low on a CIGSe surface fabricated by two-step selenization. In this work, a solution-processed surface treatment based on spin-coating GaCl3solution onto a CIGSe surface was applied to increase the Ga content on the surface. XPS, XRD, Raman spectroscopy, and band gap extraction based on the external quantum efficiency response demonstrated that GaCl3post deposition treatment (GaCl3–PDT) can be used to enhance the Ga content on the surface of a CIGSe absorber. Meanwhile, a solution-processed surface treatment with KSCN (KSCN–PDT) was employed to form a transmission barrier for holes by moving the valence band maximum downward and decreasing the interface recombination between the CdS and CIGSe layers. Admittance spectroscopy results revealed that deep defects were passivated by GaCl3–PDT or KSCN–PDT. By applying the combination of GaCl3–PDT and KSCN–PDT, a champion device was realized that exhibited an efficiency of 13.5% with an improved VOCof 610 mV. Comparing the efficiency of the untreated CIGSe solar cells (11.7%), the CIGSe device efficiency with GaCl3–PDT and KSCN–PDT exhibited 15% enhancement.

•An innovative inner spiral finned tube is proposed to improve LFSR efficiency.•The spiral fin enhances the fluid mixing and hence the improvement of heat transfer.•The inner spiral finned tube lead to a 29% increase in Nuand a 16% improvement in JF.

A numerical simulation using FLUENT was used to monitor field temperatures under a film-soil system of potato sowing with white film mulching and soil covering the seed band in the Dingxi district. The results showed that, with an increase in the solar altitude angle, the surface temperatures of the ridge increased gradually from East to West, and the heat transferred from the surface to the deep soil. It was found that soil temperatures within 20 cm of the ridge surface was greatly affected by solar radiation and air temperature changes. With an increase in depth, the lag effect on temperature changes became more prominent. Soil temperatures under mulching film on the seed band were lower than those under mulching film without covering soil, which indicates that covering the seed band with soil in using film mulching can effectively avoid scorching the buds and seedlings due to high temperatures. At 16:46 h, soil temperature at 5 cm below the surface of the East and West seed bands reached their peak temperatures of 312.09 and 311.0 K, respectively. At 19:16 h, soil temperatures at 5, 10, 15, 20 and 25 cm depth in seed bands were 309.28, 304.94, 298.05, 293.64, 290.49 and 308.66, 303.42, 297.70, 292.70, 289.67 K, respectively. Simulated soil temperatures at different depths in seed bands of potato ridge for 5 consecutive sunny days were compared with the measured temperatures. The relative error was less than 5.5%, indicating that the simulation method was reliable. This study is of significance to the growth-promoting techniques of mulched potato sowing, and in constructing a film-soil system which facilitates potato sprouting.

The two-step process of electrodeposition and selenization is one of the most effective methods for producing CIGSe and CZTSe solar cells at a low cost. However, it is difficult to prepare the ultrathin CIGSe absorber by electrodeposition due to the nonuniform deposition of Cu on the Mo substrate. In this study, Cu was deposited on a Sb film instead of a Mo film, and the 3D growth mode of Cu was changed. Uniform and smooth ultrathin Cu films were fabricated on the Sb film using a pulse frequency over a range from 1000 to 10,000 Hz and a pulse current density ranging from 31.25 to 62.5 mA/cm2. Owing to the improved uniformity of Cu/In/Ga films, the thickness of the CIGSe absorber was reduced from 2 to 0.36 μm with Sb incorporation. In addition, the effects of Sb-doping on the CIGSe absorbers and the device performance were investigated. The crystallinity of the CIGSe films was improved, and the interface recombination of the solar cells was reduced by Sb incorporation. Ultimately, CIGSe thin-film solar cells with efficiencies of 5.25 and 11.27% were obtained with CIGSe absorber thicknesses of 0.36 and 1.2 μm, respectively.

Plasma separation, rich in biomarkers crucial for diagnosis, is conventionally achieved via high-speed centrifugation, a method hindered by its blood usage, lengthy processes, and complex operations, which delays detection. We introduced a novel real-time blood sensing method based on a Janus membrane and enzymes @MOFs. Asymmetric driving of the janus membrane can realize spontaneous separation of plasma and prevent hemolysis during direct separation. Glucose oxidase (GOx), uric acid oxidase (UOx) and horseradish peroxidase (HRP) were encapsulated in a hydrophilic organometallic framework (MOFs) to construct an enzyme cascade nanoreactor. Embedding enzyme in hydrophilic MOFs not only retains the natural conformation of free enzyme but also improves the brittleness of enzyme, endows MOFs with new biological functions, and expands its sensing application. Using 3,3′,5,5′-tetramethylbenzidine (TMB) as a chromogen and a custom app for color interpretation, we achieved real-time visualization of glucose (Glu) and uric acid (UA) at a 50 μM limit. The system accurately analyzed serum samples, matching commercial kits and showing promise for portable, personalized diagnostics.

This study aims to achieve intelligent fusion and unified modeling to meet the requirements of multi-source and heterogeneous big data granulation for knowledge discovery in the field of water resources. The paper focuses on decision-making data granulation and knowledge discovery driven by big data in the field of water resources. It utilizes a combination of domain numerical simulation and model verification to systematically investigate decision-oriented big data multi-granularity granulation and knowledge discovery. The study reveals the mechanism and law of the transformation of management and decision-making paradigm driven by big data. This study results include the development of a granulation mechanism and a semantic fusion method for multi-source and heterogeneous big data, a multi-scale granular structure for big data, multi-granularity feature discovery and granulation method, and a multi-granularity uncertainty reasoning and knowledge discovery method. The proposed dynamic big data fusion and knowledge discovery approach effectively supports big data granulation and knowledge discovery in water resource decision-making. The study found that the proposed dynamic big data multi-granularity fusion method outperforms existing dynamic big data correlation analysis methods and greatly reduces data processing time.

The era of big data has brought new challenges to chemical enterprises. In order to maximize the benefits, enterprises are considering to implement intelligent service technology into traditional production systems to improve the level of intelligence in business. This paper proposes a service framework based on big data driven prediction, which includes information perception layer, information application layer and big data service layer. In this paper, the composition of big data service layer is described in detail, and a sales predicting method based on neural network is introduced. The salability of products is divided, and the qualitative economic production volume mechanism is finally given. Based on the framework, an intelligent service system for enterprises with the characteristics of mass production is implemented. Experimental results show that the big data service framework can support chemical enterprises to make decisions to reduce costs, and provides an effective method for Smart Product Service System (PSS).

In order to measure environmental parameters in a better way, we use WiFi technology and design a new environmental monitoring system. This system uses humiture sensor and optical sensor to collect humiture and optical data, through wireless communication module in communication with the host computer. It accepts the collection instruction and sends real-time data to the host computer. This paper shows the structure diagram of system, the circuit diagram of control node and sensor node, the flow chart of programming and the user interface of PC. Generally, this system is easily-operated, rapid, and functional thus has the potential to be widely applicated.

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Internal metallurgical defects and poor mechanical properties and surface quality of the formed parts are the most important challenges of metal micro-droplets deposition manufacturing technology. Lack of strong coalescence between neighboring droplets and the blocking effects of periodic ripples on the fusion process are major sources of abovementioned problems. To address this issue, a tungsten inert gas (TIG) welding arc was introduced to pre-melt the material below the droplet impacting location, thus, one droplet train will be deposited on a curved molten pool surface to fabricate deposited layers in an additive approach. In the present work, a numerical model based on the computational fluid dynamics (CFD) method was developed to investigate the dynamic behaviors of successive droplets’ impact and coalescence on the molten pool created by a tilted TIG welding arc, and focuses on the effect of the offset distance between the impacting point of droplet and the longitudinal plane of molten pool on the deposition morphology and the impact-induced molten pool behaviors. The simulated tracks exhibit regular scaly shapes at different offset distances, which is validated against the corresponding experiments. The results indicated that as the lateral offset distance increases, the symmetric spreading and recoiling of the subsequent droplets on the pre-existing bead will be broken due to the inclined and curved solidification front morphologies, the inclined front morphologies are caused by the increased growth rate of the solidification front at the impact zone. With an increased lateral offset distance, the volume of the molten pool decreases, the width of the rear molten pool increases slightly. The calculated solidification parameters are found to be dependent of the offset distance, and vary significantly at the onset of solidification at different portions of the molten pool. The scientific findings provide useful insights for further researches of TIG-assisted DDM.

To reduce the size and the weight of heat exchangers, vortex generators (VGs) were punched on fin surface to improve the fin heat transfer performance. This paper is focused on the optimal fin spacing for three-row flat tube bank fin mounted with VGs. The results show, for commonly used fin materials and fin thickness, the optimal fin spacing is about 2 mm in industrial application for the configuration of tube bank fin studied.To reduce the size and the weight of heat exchangers, vortex generators (VGs) were punched on fin surface to improve the fin heat transfer performance. This paper is focused on the optimal fin spacing for three-row flat tube bank fin mounted with VGs. The results show, for commonly used fin materials and fin thickness, the optimal fin spacing is about 2 mm in industrial application for the configuration of tube bank fin studied.