Machine Learning Algorithms for Intelligent Decision Recognition and Quantification of Cr(III) in Chromium Speciation.

Cr(III) is a common oxidation state of chromium, and its presence in the environment can occur naturally or as a result of human activities, such as industrial processes, mining, and waste disposal. This article explores the application of machine learning algorithms for the intelligent decision recognition and quantification of Cr(III) in chromium speciation. Three different machine learning models, namely, the Decision Tree (DT) model, the PCA-SVM (Principal Component Analysis-Support Vector Machine) model, and the LDA (Linear Discriminant Analysis) model, were employed and evaluated for accurate and efficient classification of chromium concentrations based on their fluorescence responses. Furthermore, stepwise multiple linear regression analysis was utilized to achieve a more precise quantification of trivalent chromium concentrations through fluorescence visualization. The results demonstrate the potential of machine learning algorithms in accurately detecting and quantifying Cr(III) in chromium speciation with implications for environmental and industrial applications in chromium detection and quantification. The findings from this research pave the way for further exploration and implementation of these models in real-world scenarios, offering valuable insights into various environmental and industrial contexts.

Morphology Control of Electrospun Brominated Butyl Rubber Microfibrous Membrane.

Brominated butyl rubber (BIIR) is a derivative of butyl rubber, with the advantage of high physical strength, good vibration damping performance, low permeability, aging resistance, weather resistance, etc. However, it is hard to avoid BIIR fiber sticking together due to serious swelling or merging, resulting in few studies on BIIR electrospinning. In this work, brominated butyl rubber membrane (mat) with BIIR microfiber has been prepared by electrospinning. The spinnability of elastomer BIIR has been explored. The factors influencing the morphology of BIIR microfiber membranes have been studied, including solvent, electrospinning parameters, concentration, and the rheological property of electrospinning solution. The optimal parameters for electrospinning BIIR have been obtained. A BIIR membrane with the ideal microfiber morphology has been obtained, which can be peeled from aluminum foil on a collector easily without being broken. Anti-bacterial property, the electrical conductivity of these membranes, and the mechanical properties of these samples were studied. The optimized BIIR electrospinning solution is Bingham fluid. The results of these experiments show that a BIIR membrane can be used in the field of medical prevention, wearable electronics, electronic skin, and in other fields that require antibacterial functional polymer materials.

Progress in the Synthesis and Application of Transparent Conducting Film of AZO (ZnO:Al).

Due to the excellent performance and low cost of the new aluminum-doped zinc oxide (AZO) film, it is expected to replace the mature indium-doped tin oxide (ITO) film. The research status and progress of AZO transparent conductive films are summarized in this review. Moreover, the structure, optoelectronic properties, and conductive mechanism of AZO thin films are also detailed. The thin films' main preparation processes and the advantages and disadvantages of each process method are mainly discussed, and their application fields are expounded. AZO thin films with multicomponent composite structures are one of the promising development directions in transparent conductive oxide (TCO) thin films. The development of various preparation processes has promoted the production and application of thin films on a broad scale. Finally, some improvement schemes have been proposed to improve the comprehensive performance of the film. The industrialization prospects of the AZO film, as well as its great development potential in the digital world, are discussed.

Controllable Synthesis of PtIrCu Ternary Alloy Ultrathin Nanowires for Enhanced Ethanol Electrooxidation.

Rational design and controllable synthesis of catalysts with unique structure and composition are effective ways to promote electrocatalytic ethanol oxidation, thus contributing the direct ethanol fuel cells to gain ground. Herein, 2.5 nm-thin PtIrCu ternary alloy ultrathin nanowires (UNWs) with high-density planar defects are synthesized via oriented attachment with the assistance of H2. By adjusting the contents of Ir and Cu atoms, we find that the structure of the products changed from nanowires (NWs) to nanoparticles with the increase of Ir content. Density functional theory calculations show that when Cu atoms are replaced by Ir atoms, the vacancy formation energy of Pt atoms is increased, making the Pt atoms difficult to be activated by H2, which is not conducive to the formation of a one-dimensional structure. The optimal Pt43Ir32Cu25 UNWs achieve excellent ethanol electrooxidation reaction activity (1.05 A·mg-1Pt and 1.67 mA·cm-2), for it can significantly reduce the onset potential and improve the ability of CO anti-poisoning. The significant improvement in catalytic performance is attributed to the synergistic effect of the alloy and the NW structure with high-density planar defects.

Highly selective and sensitive determination of ceftriaxone sodium using nitrogen-rich carbon dots based on ratiometric fluorescence.

Selective and sensitive determination of ceftriaxone sodium (CTR) trace residues is of great importance for food safety and environmental protection. Herein, a determination method based on ratiometric fluorescence and colorimetric method with nitrogen-rich carbon dots as fluorophore is reported. The functional surfaces of indole-derived carbon dots (I-CDs) containing nitrogen and carbon groups can be selectively bound to CTR by electrostatic forces, leading to a hindered conjugation system and deprotonation of the amine on the pyrrole ring, resulting in a distinct variety in fluorescence and absorption wavelength and intensity. With the addition of CTR, the fluorescence at 577 nm can be selectively quenched, accompanied by a new emission peak appeared at 507 nm. The limits of detection (LODs) were estimated to be 19.7 nM and 78.0 nM based on the ratiometric fluorescence method and colorimetric method, respectively. Finally, the in situ visual quantitative determination of CTR using this nanosensor was achieved by combining with the color recognizer of a smartphone, and the method was further validated by spike and recovery test in real water samples including milk, seawater, and tap water.

Mechanism of Potassium Release from Feldspar by Mechanical Activation in Presence of Additives at Ordinary Temperatures.

To improve the potassium availability of feldspar at ordinary temperatures, the mechanical grinding and addition of sodium hydroxide/salts were employed to study the effects of mechanical activation and strong alkali addition on particle characteristics, water-soluble potassium, and the available potassium of feldspar. A laser particle size analyzer was utilized for the direct determination of particle size distribution (PSD) using ground samples. The Brunauer-Emmett-Teller (BET) method was employed for specific surface areas. X-ray diffraction (XRD) was employed for structural characterization, scanning electron microscopy (SEM) for morphology exploration, and energy dispersive spectroscopy (EDS) to determine the chemical composition of potassium feldspar powder. The results revealed that the mechanical activation of potassium feldspar could reduce the particle size and produce agglomerated nanoparticles in the later period. The addition of NaOH and sodium salt did not cause agglomeration, and NaOH dissolved the nanoparticles. The water-soluble potassium content of feldspar in each treatment increased during mechanical grinding, from 21.64 mg kg-1 to 1495.81 mg·kg-1, by adding NaOH 5% weight of potassium feldspar powder and to 3044.08 mg·kg-1 by adding NaOH 10% weight with effects different from those of mechanical shaking. By comparison, only 162.93 mg·kg-1 water-soluble potassium was obtained by adding NaOH 5% weight. The dissolved potassium in the former case was significantly higher than in the latter, and the addition of NaOH and sodium salts significantly enhanced the water-soluble potassium contents due to ion exchange. Furthermore, the addition of sodium hydroxide improved the water-soluble potassium due to its mechanochemical action on potassium feldspar. The mechanical energy changed the crystal structure of potassium feldspar, explaining the increase in available potassium. The addition of sodium salts did not promote change in the feldspar's structure, thereby did not raise the available potassium content. The reason for this was related to the mechanochemical action on sodium hydroxide and feldspar, which could promote the dissolution of fine particles, thereby incrementing the available potassium.

UAV Localization Algorithm Based on Factor Graph Optimization in Complex Scenes.

With the increasingly widespread application of UAV intelligence, the need for autonomous navigation and positioning is becoming more and more important. To solve the problem that UAV cannot perform localization in complex scenes, a new multi-source fusion framework factor graph optimization algorithm is used for UAV localization state estimation in this paper, which is based on IMU/GNSS/VO multi-source sensors. Based on the factor graph model and the iSAM incremental inference algorithm, a multi-source fusion model of IMU/GNSS/VO is established, including the IMU pre-integration factor, IMU bias factor, GNSS factor, and VO factor. Mathematical simulations and validations on the EuRoC dataset show that, when the selected sliding window size is 30, the factor graph optimization (FGO) algorithm can not only meet the requirements of real time and accuracy at the same time, but it also achieves a plug-and-play function in the event of local sensor failures. Finally, compared with the traditional federated Kalman algorithm and the adaptive federated Kalman algorithm, the positioning accuracy of the FGO algorithm in this paper is improved by 1.5-2-fold, and can effectively improve autonomous navigation system robustness and flexibility in complex scenarios. Moreover, the multi-source fusion framework in this paper is a general algorithm framework that can satisfy other scenarios and other types of sensor combinations.

Research on UAV Robust Adaptive Positioning Algorithm Based on IMU/GNSS/VO in Complex Scenes.

As an important component of autonomous intelligent systems, the research on autonomous positioning algorithms used by UAVs is of great significance. In order to resolve the problem whereby the GNSS signal is interrupted, and the visual sensor lacks sufficient feature points in complex scenes, which leads to difficulties in autonomous positioning, this paper proposes a new robust adaptive positioning algorithm that ensures the robustness and accuracy of autonomous navigation and positioning in UAVs. On the basis of the combined navigation model of vision/inertial navigation and satellite/inertial navigation, based on ESKF, a multi-source fusion model based on a federated Kalman filter is here established. Furthermore, a robust adaptive localization algorithm is proposed, which uses robust equivalent weights to estimate the sub-filters, and then uses the sub-filter state covariance to adaptively assign information sharing coefficients. After simulation experiments and dataset verification, the results show that the robust adaptive algorithm can effectively limit the impact of gross errors in observations and mathematical model deviations and can automatically update the information sharing coefficient online according to the sub-filter equivalent state covariance. Compared with the classical federated Kalman algorithm and the adaptive federated Kalman algorithm, our algorithm can meet the real-time requirements of navigation, and the accuracy of position, velocity, and attitude measurement is improved by 2-3 times. The robust adaptive localization algorithm proposed in this paper can effectively improve the reliability and accuracy of autonomous navigation systems in complex scenes. Moreover, the algorithm is general-it is not intended for a specific scene or a specific sensor combination- and is applicable to individual scenes with varied sensor combinations.

Effects of artemisinin on photosystem II performance of Microcystis aeruginosa by in vivo chlorophyll fluorescence.

Effects of artemisinin (derived from Artemisia annua) on the photosynthetic activity of Microcystis aeruginosa was investigated by using chlorophyll a (Chl a) fluorescence transient O-J-I-P and JIP-test after exposure to elevated artemisinin concentration. High artemisinin concentration resulted in a significant suppression in photosynthesis and respiration. Results showed that the OJIP curves flattened and the maximal fluorescence yield reached at the J step under artemisinin stress. The decreased values of the energy needed for the RCs' closure (Sm) and the number of oxidation and reduction (N) suggested that the reduction times of primary bound plastoquinone (Q(A)) was also decreased. The absorption flux (ABS/RC) per photosystem II (PSII) reaction center and the electron transport flux (ET(0)/RC) decreased with increasing artemisinin concentration. Excess artemisinin had little effect on the trapping flux (TR(0)/RC). The results showed that the decrease of photosynthesis in exposure to excess artemisinin may be a result of the inactivation of PSII reaction centers and the inhibition of electron transport in the acceptor side.

Isolation and identification of an anti-algal compound from Artemisia annua and mechanisms of inhibitory effect on algae.

The goals of this work were to isolate and identify an anti-algal compound from extracts of Artemisia annua and study its mode of action on Microcystis aeruginosa. The anti-algal compound was isolated from the extracts using column chromatography and activity-guided fractionation methods. Artemisinin with strong anti-algal activity was identified by gas chromatography-mass spectrometry and (1)H Nuclear Magnetic Resonance. The EC(50) of artemisinin on M. aeruginosa was 3.2mg L(-1). Artemisinin decreased the soluble protein content and increased the superoxide dismutase activity and ascorbic acid content of M. aeruginosa, but exerted no effect on soluble sugar content. The results suggested the mode of action of artemisinin on algae may primarily be the increasing level of reactive oxygen species in algae cells. The results of our research could aid in the development of new anti-algal substances and lead to further study of mechanisms of inhibitory effect on algae.

Acid tolerance of an acid mine drainage bioremediation system based on biological sulfate reduction.

The acid tolerance response of an AMD bioremediation system based on sulfate reduction was investigated. Efficient sulfate reduction was observed with a maximum sulfate reduction rate of 12.3±0.8 mg L(-1) d(-1) and easily available organic carbon was released during high acid treatment with an initial pH of 2.0. The rapid increase in sulfate reduction was observed when the extreme acid treatment with an initial pH of 1.0 was stopped. Column experiment on acid shock showed that efficient sulfate reduction was maintained while precipitation of Cu or Zn still occurred during extreme or high acid shock. More than 98% of Cu and 85% of Zn were removed in the high acid column experiment with influent pH of 2.0. The majority bacteria in the remediation system used for high acid drainage belonged to genera Clostridiaceae, Eubacterium, Pseudobutyrivibrio, and Clostridium. These findings showed high acid tolerance of the straw remediation system.

[The tendency of physiological and psychological change of the armored vehicle drivers working continuously in hot environment].

OBJECTIVE: To probe the tendency of physiological and psychological change of armored vehicle drivers working continuously in hot environment. METHODS: Ten cross-designed standard subjects were divided into control group and driver group. The driver group worked continuously in 32 degrees C approximately 38 degrees C and RH 50% approximately 80% environment. Heart rate, body temperature, systolic blood pressure and pulse pressure were synchronously and dynamically determined during work. Psychological parameters such as profile of mood states (POMS) questionnaire, serial addition/subtraction (SAS) and two-digit search (TDS) selected from neurobehavioral evaluation system (NES) before and after work were also tested. RESULTS: The curves of the four main physiological parameters rapidly synchro-rose to a peak at (36 +/- 3) min, whereafter the curves descended smoothly. At (144 +/- 8) min, the curves climbed up to the second peak. The determination of the behavioral psychology revealed that the degree of fatigue of the drivers increased gradually when the working time prolonged, and the grip descended by great extent, excitement reduced markedly after work, but the negative mood, such as confusion and depression were increased, error of visual apperceive-operation was increased, right decreased, intelligence reduced, rapidity and delicacy of movement reduced. CONCLUSION: The physiological parameters of armored vehicle drivers working continuously in the hot condition appeared double-peak effect, the 1st peak was at (36 +/- 3) min, and the body was in mobilizing stage. Whereafter, the body was in smooth stage. And at (144 +/- 8) min, when the 2nd peak appeared, the body then was in physiological tolerance limit stage.