Comparative study of electroplating sludge reutilization in China: environmental and economic performances.

Harmless disposal and reutilization of electroplating sludge (ES) attract growing interests due to the high content of heavy metals, which requires economical-affordable and environmentally friendly processing technologies. Main reutilization alternatives in China, i.e., acid leaching, bioleaching, smelting, ironmaking blast furnace co-processing (IBFC), and cement kiln co-processing (CKC), were evaluated and compared via life cycle assessment (LCA) and life cycle costing (LCC) methods. In addition, the heavy metal recovery potential of these scenarios was also evaluated to focus on the sustainable use of metal resources. LCA results show that acid leaching outperforms other scenarios due to the environmental benefits originating from recovering heavy metals, while smelting exhibits the worst due to high energy consumption. The environmental contribution analysis reveals that the product nickel sulfate has a significant positive impact on acid leaching and bioleaching scenarios, and energy consumption is the key factor for smelting, IBFC, and CKC. LCC results show that bioleaching outperforms others, while CKC performs the worst because only inorganic materials are utilized. Bioleaching has the lowest externality cost while CKC has the highest. The heavy metal recovery assessment indicates that bioleaching exhibits the greatest potential with recovery rates of 99%, 99%, 93%, 96%, and 95% for Cu, Cr, Ni, Zn, and Fe, respectively. In contrast, the target heavy metal recovery rate for both acid leaching and smelting is 93%. Acid leaching and bioleaching scenarios are more advantageous from a comprehensive comparison.

Current oscillation elimination for the helicopter transient electromagnetic inverter based on pole configuration.

In a helicopter transient electromagnetic system, the quality of the transmitting-current waveform will affect the geological exploration effect. In this paper, a helicopter TEM inverter, based on a single-clamp source and pulse width modulation technology, is designed and analyzed. Besides, it finds that there will be current oscillation in the early measuring stage. For this problem, first, the factors that cause the current oscillation are analyzed. Then, it is proposed to apply the RC snubber to eliminate this current oscillation. Since the imaginary part of the pole is the essence of oscillation, configuring the pole can eliminate the current oscillation. By establishing the early measuring stage system model, the characteristic equation of the load current with the snubber circuit is deduced. Next, the characteristic equation is solved by the exhaustive method and the root locus method to obtain the parametric region that eliminates the oscillation. Finally, through simulation and experimental verification, the proposed snubber circuit design method can be used to eliminate the early measuring stage current oscillation. Compared to the method of switching into the damping circuit, it can achieve the same performance, more important is that there is no switching action and it is easy to achieve.

Fungal CFEM effectors negatively regulate a maize wall-associated kinase by interacting with its alternatively spliced variant to dampen resistance.

The fungus Fusarium graminearum causes a devastating disease Gibberella stalk rot of maize. Our knowledge of molecular interactions between F. graminearum effectors and maize immunity factors is lacking. Here, we show that a group of cysteine-rich common in fungal extracellular membrane (CFEM) domain proteins of F. graminearum are required for full virulence in maize stalk infection and that they interact with two secreted maize proteins, ZmLRR5 and ZmWAK17ET. ZmWAK17ET is an alternative splicing isoform of a wall-associated kinase ZmWAK17. Both ZmLRR5 and ZmWAK17ET interact with the extracellular domain of ZmWAK17. Transgenic maize overexpressing ZmWAK17 shows increased resistance to F. graminearum, while ZmWAK17 mutants exhibit enhanced susceptibility to F. graminearum. Transient expression of ZmWAK17 in Nicotiana benthamiana triggers hypersensitive cell death, whereas co-expression of CFEMs with ZmWAK17ET or ZmLRR5 suppresses the ZmWAK17-triggered cell death. Our results show that ZmWAK17 mediates stalk rot resistance and that F. graminearum delivers apoplastic CFEMs to compromise ZmWAK17-mediated resistance.

Environmental and economic assessment of rural domestic waste gasification models in China.

The dispersed sources and inconvenient transportation of rural domestic waste (RDW) lead to difficult centralized treatment. Gasification is suitable for decentralized waste treatment, which can effectively avoid RDW long-distance transportation and reduce dioxin emissions compared with small-scale incineration. Hence, economically-affordable and environmentally-friendly RDW treatment models with different gasification scales are required, and village, town and county models were compared via life cycle assessment (LCA) and life cycle cost (LCC) methods in this study. Furthermore, scenario analysis investigated waste sorting based on two food waste (FW) treatment technologies, different FW separate collection efficiency, and electricity recovery to explore the environmental and economic improvement potentials of three models. LCA results show that electricity consumption and direct emissions are significant contributors to environmental impacts, and the county model outperforms village and town models. Moreover, transportation accounts for 6% of the overall environmental impact in the county model. Scenario analysis reveals that waste sorting and electricity recovery can reduce the overall environmental impact by 29% to 146% for three models. LCC results demonstrate that the town model delivers the lowest economic cost, while the village model is the highest. In scenario analysis, resource utilization of FW and electricity recovery of other waste exhibit promising economic benefits. The findings provide comprehensive references for sustainable RDW treatment.

The fault detection of transmitting current encoded by m-sequence using triple-correlation function in helicopter-borne electromagnetic method.

An m-sequence is applied to the helicopter-borne electromagnetic method system for the first time, and there are many problems to be solved, one of which is the detection of the quality of the transmitting current waveform, which directly affects the resource survey results. In this research, we found that the triple-correlation function (TCF) can reveal the bit integrity characteristics of the m-sequence encoded transmitting current. On this basis, this paper proposes to extract the three-dimensional information of the normalized TCF plot by using a peak detection method and, then, proposes to use a dual-threshold method to clarify the detection results. The whole process realizes the fault detection of the transmitting current waveform. We propose a reasonable transmitting current modeling method and conduct 1200 random experiments in 12 groups. The statistics of the experimental results show that when the number of missing bits is 1, 2, 4, and 8, the fault detection accuracy can reach more than 83%. A comparative experiment using the Field Programmable Gate Array. in the laboratory validates the feasibility of the fault detection method. This method is beneficial to improve the quality of detection data and avoid economic losses caused by invalid detection flights.

Interpretability-Based Multimodal Convolutional Neural Networks for Skin Lesion Diagnosis.

Skin lesion diagnosis is a key step for skin cancer screening, which requires high accuracy and interpretability. Though many computer-aided methods, especially deep learning methods, have made remarkable achievements in skin lesion diagnosis, their generalization and interpretability are still a challenge. To solve this issue, we propose an interpretability-based multimodal convolutional neural network (IM-CNN), which is a multiclass classification model with skin lesion images and metadata of patients as input for skin lesion diagnosis. The structure of IM-CNN consists of three main paths to deal with metadata, features extracted from segmented skin lesion with domain knowledge, and skin lesion images, respectively. We add interpretable visual modules to provide explanations for both images and metadata. In addition to area under the ROC curve (AUC), sensitivity, and specificity, we introduce a new indicator, an AUC curve with a sensitivity larger than 80% (AUC_SEN_80) for performance evaluation. Extensive experimental studies are conducted on the popular HAM10000 dataset, and the results indicate that the proposed model has overwhelming advantages compared with popular deep learning models, such as DenseNet, ResNet, and other state-of-the-art models for melanoma diagnosis. The proposed multimodal model also achieves on average 72% and 21% improvement in terms of sensitivity and AUC_SEN_80, respectively, compared with the single-modal model. The visual explanations can also help gain trust from dermatologists and realize man-machine collaborations, effectively reducing the limitation of black-box models in supporting medical decision making.

A two-layer nested heterogeneous ensemble learning predictive method for COVID-19 mortality.

The COVID-19 epidemic has had a great adverse impact on the world, having taken a heavy toll, killing hundreds of thousands of people. In order to help the world better combat COVID-19 and reduce its death toll, this study focuses on the COVID-19 mortality. First, using the multiple stepwise regression analysis method, the factors from eight aspects (economy, society, climate etc.) that may affect the mortality rates of COVID-19 in various countries is examined. In addition, a two-layer nested heterogeneous ensemble learning-based prediction method that combines linear regression (LR), support vector machine (SVM), and extreme learning machine (ELM) is developed to predict the development trends of COVID-19 mortality in various countries. Based on data from 79 countries, the experiment proves that age structure (proportion of the population over 70 years old) and medical resources (number of beds) are the main factors affecting the mortality of COVID-19 in each country. In addition, it is found that the number of nucleic acid tests and climatic factors are correlated with COVID-19 mortality. At the same time, when predicting COVID-19 mortality, the proposed heterogeneous ensemble learning-based prediction method shows better prediction ability than state-of-the-art machine learning methods such as LR, SVM, ELM, random forest (RF), long short-term memory (LSTM) etc.

Phosphorylation of MtRopGEF2 by LYK3 mediates MtROP activity to regulate rhizobial infection in Medicago truncatula.

The formation of nitrogen-fixing no dules on legume roots requires the coordination of infection by rhizobia at the root epidermis with the initiation of cell divisions in the root cortex. During infection, rhizobia attach to the tip of elongating root hairs which then curl to entrap the rhizobia. However, the mechanism of root hair deformation and curling in response to symbiotic signals is still elusive. Here, we found that small GTPases (MtRac1/MtROP9 and its homologs) are required for root hair development and rhizobial infection in Medicago truncatula. Our results show that the Nod factor receptor LYK3 phosphorylates the guanine nucleotide exchange factor MtRopGEF2 at S73 which is critical for the polar growth of root hairs. In turn, phosphorylated MtRopGEF2 can activate MtRac1. Activated MtRac1 was found to localize at the tips of root hairs and to strongly interact with LYK3 and NFP. Taken together, our results support the hypothesis that MtRac1, LYK3, and NFP form a polarly localized receptor complex that regulates root hair deformation during rhizobial infection.

A Facilitatory Effect of Perceptual Incongruity on Target-Source Matching in Pictorial Metaphors of Chinese Advertising: EEG Evidence.

Using evoked response potentials, we investigated the implicit detection of incongruity during target-source matching in pictorial metaphors of Chinese advertising. Participants saw an image of a product (the target in a visual metaphorical relationship), and then made a same-different judgment in response to a second image (the source in a visual metaphorical relationship) which was (in)congruous to the first image in terms of shape and/or function. We collected behavioral (button-press reaction time and accuracy), and neural (N270, delta and theta band activity) measures. The time-frequency analysis showed faster processing of incongruous visual information. Moreover, shape and conceptual incongruity were associated with increased N270 amplitude as well as delta (1-3 Hz) and theta (4-8 Hz) band power. Noticeably, compared with conceptual incongruity, shape incongruity evoked a larger N270 amplitude and stronger delta and theta band oscillation. In addition, the average topographical analysis revealed a frontal and central distribution of the power activity. The analysis of attitudes towards the advertising metaphor pictures also proved the supportive role played by incongruity. In conclusion, incongruity facilitates target-source matching in pictorial metaphors of Chinese advertising. The findings obtained from the study are important to metaphor designs of advertising pictures.

The spatiotemporal control of KatG2 catalase-peroxidase contributes to the invasiveness of Fusarium graminearum in host plants.

Reactive oxygen species (ROS) are involved in the pathogen-host interactions, and play a Janus-faced role in the resistance and susceptibility of plants to biotrophic and necrotrophic pathogens. The ascomycete fungus Fusarium graminearum causes hazardous wheat Fusarium head blight worldwide. Deletion of the putative secreted catalase-peroxidase gene in F. graminearum, KatG2, reduced the virulence in wheat spike infection. However, it remains unclear when and where KatG2 scavenges ROS during the invasion of wheat. In this study, we delineate the change in ROS levels in the transition of the infection phase under microscopic observation. Correspondingly, the pathogen switches its strategy of infection with temporal and spatial regulation of KatG2 to counteract oxidative stress generated by host plant cells. With the native promoter-driven KatG2-mRFP strain, we show that KatG2-mRFP expression was induced in planta and accumulated in the infection front region at the early infection stage. In contrast to its ubiquitous cellular localization in runner hyphae, KatG2-mRFP is exclusively located on the cell wall of invading hyphal cells, especially at the pathogen-host cellular interface. Using posttranslational modification analysis, we found that asparagine residues at the 238 and 391 positions of KatG2 could be modified by N-glycosylation and that these two residues are required for KatG2 accumulation and cell wall localization in planta.

A Trace Carbon Monoxide Sensor Based on Differential Absorption Spectroscopy Using Mid-Infrared Quantum Cascade Laser.

Carbon monoxide (CO), as a dangerous emission gas, is easy to accumulate in the complex underground environment and poses a serious threat to the safety of miners. In this paper, a sensor using a quantum cascade laser with an excitation wavelength of 4.65 µm as the light source, and a compact multiple reflection cell with a light path length of 12 m is introduced to detect trace CO gas. The sensor adopts the long optical path differential absorption spectroscopy technique (LOP-DAST) and obtains minimum detection limit (MDL) of 108 ppbv by comparing the residual difference between the measured spectrum and the Voigt theoretical spectrum. As a comparison, the MDL of the proposed sensor was also estimated by Allan deviation; the minimum value of 61 ppbv is achieved while integration time is 40 s. The stability of the sensor can reach 2.1 × 10-3 during the 2 h experimental test and stability of 1.7 × 10-2 can still be achieved in a longer 12 h experimental test.

A SFTD Algorithm for Optimizing the Performance of the Readout Strategy of Residence Time Difference Fluxgate.

Residence time difference (RTD) fluxgate sensor is a potential device to measure the DC or low-frequency magnetic field in the time domain. Nevertheless, jitter noise and magnetic noise severely affect the detection result. A novel post-processing algorithm for jitter noise reduction of RTD fluxgate output strategy based on the single-frequency time difference (SFTD) method is proposed in this study to boost the performance of the RTD system. This algorithm extracts the signal that has a fixed frequency and preserves its time-domain information via a time⁻frequency transformation method. Thereby, the single-frequency signal without jitter noise, which still contains the ambient field information in its time difference, is yielded. Consequently, compared with the traditional comparator RTD method (CRTD), the stability of the RTD estimation (in other words, the signal-to-noise ratio of residence time difference) has been significantly boosted with sensitivity of 4.3 µs/nT. Furthermore, the experimental results reveal that the RTD fluxgate is comparable to harmonic fluxgate sensors, in terms of noise floor.

An improved support vector machine-based diabetic readmission prediction.

BACKGROUND AND OBJECTIVE: In healthcare systems, the cost of unplanned readmission accounts for a large proportion of total hospital payment. Hospital-specific readmission rate becomes a critical issue around the world. Quantification and early identification of unplanned readmission risks will improve the quality of care during hospitalization and reduce the occurrence of readmission. In clinical practice, medical workers generally use LACE score method to evaluate patient readmission risks, but this method usually performs poorly. With this in mind, this study presents a novel method combining support vector machine and genetic algorithm to build the risk prediction model, which simultaneously involves feature selection and the processing of imbalanced data. This model aims to provide decision support for clinicians during the discharge management of patients with diabetes. METHOD: The experiments were conducted from a set of 8756 medical records with 50 different features about diabetic readmission. After preprocessing the data, an effective SMOTE-based method was proposed to solve the imbalance data problem. Further, in order to improve prediction performance, a hybrid feature selection mechanism was devised to select the important features. Subsequently, an improved support vector machine-based (SVM-based) method was developed and the genetic algorithm was used to tune the sensitive parameter of the algorithm. Finally, the five-fold cross-validation method was applied to compare the performance of proposed method with other methods (LACE score, logistic regression, naïve bayes, decision tree and feed forward neural networks). RESULTS: Experimental results indicate that the proposed SVM-based method achieves an accuracy of 81.02%, a sensitivity of 82.89%, a specificity of 79.23%, and outperforms other popular algorithms in identifying diabetic patients who may be readmitted. CONCLUSIONS: Our research can improve the performance of clinic decision support systems for diabetic readmission, by which the readmission possibility as well as the waste of medical resources can be reduced.

The N1-N2-LPC Pattern in Processing Advertising Pictorial Metaphors: An ERP Study.

We investigated what the temporal processing is of advertising pictorial metaphors. After presenting "a word of product" and "its advertising pictures," the experiment instructed participants to make a follow-up true-false judgment considering what the picture intended to suggest. A repeated-measures ANOVAs for a 2 (picture type: metaphor, non-metaphor) × 2 (prime-target condition: congruent, incongruent) × 3 (electrode site: Fz, Cz, Pz) experimental condition was conducted on three components, N1 (100-150 ms), N2 (200-300 ms), and LPC (400-600 ms and 600-1,000 ms). The results show that metaphor pictures elicited larger amplitude in N1 (broadly distributed), N2 (frontally biased) and LPC (parietally biased), roughly reflecting an entire process with an initial response to visual onsets, an early recognition of semantic violations and a prolonged reanalysis process of semantic integration. We argue that, different than verbal metaphors, this faster processing occurred due to the involvement of visual pathway.

A High Stability Time Difference Readout Technique of RTD-Fluxgate Sensors.

The performance of Residence Times Difference (RTD)-fluxgate sensors is closely related to the time difference readout technique. The noise of the induction signal affects the quality of the output signal of the following circuit and the time difference detection, so the stability of the sensor is limited. Based on the analysis of the uncertainty of the RTD-fluxgate using the Bidirectional Magnetic Saturation Time Difference (BMSTD) readout scheme, the relationship between the saturation state of the magnetic core and the target (DC) magnetic field is studied in this article. It is proposed that combining the excitation and induction signals can provide the Negative Magnetic Saturation Time (NMST), which is a detection quantity used to measure the target magnetic field. Also, a mathematical model of output response between NMST and the target magnetic field is established, which analyzes the output NMST and sensitivity of the RTD-fluxgate sensor under different excitation conditions and is compared to the BMSTD readout scheme. The experiment results indicate that this technique can effectively reduce the noise influence. The fluctuation of time difference is less than ±0.1 µs in a target magnetic field range of ±5 × 104 nT. The accuracy and stability of the sensor are improved, so the RTD-fluxgate using the readout technique of high stability time difference is suitable for detecting weak magnetic fields.

A dumbbell-shaped hybrid magnetometer operating in DC-10 kHz.

This study is motivated by the need to design a hybrid magnetometer operating in a wide-frequency band from DC to 10 kHz. To achieve this objective, a residence times difference fluxgate magnetometer (RTDFM) and an induction magnetometer (IM) have been integrated into a compact form. The hybrid magnetometer has a dumbbell-shaped structure in which the RTDFM transducer is partially inserted into the tube cores of the IM. Thus, the sensitivity of the RTDFM is significantly improved due to the flux amplification. The optimal structure, which has maximum sensitivity enhancement, was obtained through FEM analysis. To validate the theoretical analysis, the optimal hybrid magnetometer was manufactured, and its performance was evaluated. The device has a sensitivity of 45 mV/nT at 1 kHz in IM mode and 0.38 µs/nT in RTDFM mode, which is approximately 3.45 times as large as that of the single RTDFM structure. Furthermore, to obtain a lower noise performance in the entire frequency band, two operation modes switch at the cross frequency (0.16 Hz) of their noise levels. The noise level is 30 pT/√Hz in RTDFM mode and 0.07 pT/√Hz at 1 kHz in IM mode.

An Optimized Air-Core Coil Sensor with a Magnetic Flux Compensation Structure Suitable to the Helicopter TEM System.

The air-core coil sensor (ACS) is widely used as a transducer to measure the variation in magnetic fields of a helicopter transient electromagnetic (TEM) system. A high periodic emitting current induces the magnetic field signal of the underground medium. However, such current also generates a high primary field signal that can affect the received signal of the ACS and even damage the receiver. To increase the dynamic range of the received signal and to protect the receiver when emitting current rises/falls, the combination of ACS with magnetic flux compensation structure (bucking coil) is necessary. Moreover, the optimized ACS, which is composed of an air-core coil and a differential pre-amplifier circuit, must be investigated to meet the requirements of the helicopter TEM system suited to rapid surveying for shallow buried metal mine in rough topography. Accordingly, two ACSs are fabricated in this study, and their performance is verified and compared inside a magnetic shielding room. Using the designed ACSs, field experiments are conducted in Baoqing County. The field experimental data show that the primary field response can be compensated when the bucking coil is placed at an appropriate point in the range of allowed shift distance beyond the center of the transmitting coil and that the damage to the receiver induced by the over-statured signal can be solved. In conclusion, a more suitable ACS is adopted and is shown to have better performance, with a mass of 2.5 kg, resultant effective area of 11.6 m² (i.e., diameter of 0.496 m), 3 dB bandwidth of 66 kHz, signal-to-noise ratio of 4 (i.e., varying magnetic field strength of 0.2 nT/s), and normalized equivalent input noise of 3.62 nV/m².

A cytoplasmic Cu-Zn superoxide dismutase SOD1 contributes to hyphal growth and virulence of Fusarium graminearum.

Superoxide dismutases (SODs) are scavengers of superoxide radicals, one of the main reactive oxygen species (ROS) in the cell. SOD-based ROS scavenging system constitutes the frontline defense against intra- and extracellular ROS, but the roles of SODs in the important cereal pathogen Fusarium graminearum are not very clear. There are five SOD genes in F. graminearum genome, encoding cytoplasmic Cu-Zn SOD1 and MnSOD3, mitochondrial MnSOD2 and FeSOD4, and extracellular CuSOD5. Previous studies reported that the expression of SOD1 increased during infection of wheat coleoptiles and florets. In this work we showed that the recombinant SOD1 protein had the superoxide dismutase activity in vitro, and that the SOD1-mRFP fusion protein localized in the cytoplasm of F. graminearum. The Δsod1 mutants had slightly reduced hyphal growth and markedly increased sensitivity to the intracellular ROS generator menadione. The conidial germination under extracellular oxidative stress was significantly delayed in the mutants. Wheat floret infection assay showed that the Δsod1 mutants had a reduced pathogenicity. Furthermore, the Δsod1 mutants had a significant reduction in production of deoxynivalenol mycotoxin. Our results indicate that the cytoplasmic Cu-Zn SOD1 affects fungal growth probably depending on detoxification of intracellular superoxide radicals, and that SOD1-mediated deoxynivalenol production contributes to the virulence of F. graminearum in wheat head infection.

Investigation and Optimization of the Performance of an Air-Coil Sensor with a Differential Structure Suited to Helicopter TEM Exploration.

An air-coil sensor (ACS) is a type of induction magnetometer used as a transducer to measure the variations of a magnetic field. This device is widely applied in helicopter transient electromagnetic method (TEM) exploration. Most helicopter TEM explorations generate common-mode noise and require extreme ACS specifications, both of which inevitably challenge geophysical explorations. This study proposes a differential air-core coil combined with a differential pre-amplifier to reduce the common-mode noise induced in exploration surveys. To satisfy the stringent performance requirements, including the geometric parameters and electrical specifications, the physical calculations in theory and the equivalent schematic of an ACS with noise location are investigated, respectively. The theory calculation and experimental result for the optimized ACS are then compared on the basis of a differential structure. Correspondingly, an ACS is constructed with a mass, resultant effective area, 3 dB bandwidth, signal-to-noise ratio, and normalized equivalent input noise of 2.5 kg, 5.5 m² (diameter is 0.5 m), 71 kHz, 20 (the varying magnetic field strength is 1 nT/s), and 5.43 nV/m², respectively. These data are superior to those of the traditional induction sensor 3D-3. Finally, a field experiment is performed with a fabricated sensor to show a valid measurement of the time-varying magnetic field of a helicopter TEM system based on the designed ACS.