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Several global leaf area index (LAI) products were generated using neural networks, but the training dataset for the neural networks was sensor specific, and the construction of the training dataset was time consuming. In this paper, an unsupervised domain adaptation-based method was proposed to estimate LAI from the Visible Infrared Imaging Radiometer Suite (VIIRS) surface reflectance dataset based on a training dataset constructed from the Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance dataset. A transfer component analysis (TCA) algorithm was first utilized to map the MODIS and VIIRS surface reflectance into the same subspace to reduce the distribution discrepancies between the MODIS and VIIRS surface reflectance. Then, the embedded data obtained from MODIS surface reflectance dataset, along with the LAI values produced by fusing the MODIS and the Carbon cYcle and Change in Land Observational Products from an Ensemble of Satellites (CYCLOPES) products, were employed to train general regression neural networks (GRNNs). Finally, for retrieving the LAI values, the embedded data acquired from the VIIRS surface reflectance dataset was input into the trained GRNNs. For multiple field sites with different biome types, we used this developed method to retrieve LAI values based on the VIIRS surface reflectance dataset. The results indicate that, based on the training dataset built from MODIS surface reflectance dataset, the domain adaptation-based retrieval method can effectively estimate LAI values from VIIRS surface reflectance dataset. By comparison with the VIIRS and MODIS LAI products, the retrieved LAI values with TCA are more consistent with the reference LAI values acquired from high-resolution remote sensing images. The coefficient of determination (R2) and root mean square error (RMSE) of the retrieved LAI values with TCA at all selected sites are 0.88 and 0.68, respectively. Furthermore, the accuracy of the retrieved LAI values with TCA is higher than the retrieved LAI values without TCA with the R2 0.81 and the RMSE 0.79. [ABSTRACT FROM AUTHOR]

A series of nitrogen-doped graphene quantum dots decorated iodine bismuth oxide (BiOI/x%N-GQDs, x = 0,1,3,5,7,9,10) was prepared by a facial precipitation method at room temperature. Several characterizations indicated that 1–9 nm N-GQDs were evenly decorated on the surface of BiOI nanosheets. The visible light driven photocatalytic experiments showed that BiOI/9%N-GQDs possessed an excellent degradation property towards 20 mg/L methyl orange (MO), and its degradation efficiency obtained 93.11%. The results of free radical capture experiments demonstrated that h+ played a major role during the process of degrading MO. The possible photocatalytic mechanism had been proposed. Besides, BiOI/9%N-GQDs catalyst effectively degraded other organic pollutants, such as rhodamine B (RhB), methylene blue (MB), bisphenol A (BPA), and inorganic pollutant of Cr(Ⅵ). The catalytic property of BiOI/9%N-GQDs was better than those of the similar reported systems. The catalytic system of BiOI/9%N-GQDs was predicted to have good prospects in further practical applications. [Display omitted] • Nitrogen-doped graphene quantum dots (N-GQDs) with 1–9 nm were successfully prepared. • N-GQDs were evenly decorated on the surface of BiOI nanosheets (BiOI/x%N-GQDs). • BiOI/x%N-GQDs were in-situ composited by a facial precipitation method. • BiOI/9%N-GQDs showed the most obvious enhancement to visible light degrading MO. • The BiOI/9%N-GQDs could effectively degrade MO, RhB, MB, BPA or Cr(VI). [ABSTRACT FROM AUTHOR]

The synthesis of oxygen vacancy (V O) -engineered Fe 2 O 3 (Fe 2 O 3-x) nanospheres on three-dimensional reduced graphene oxide (3D rGO/Fe 2 O 3-x) is proposed via a gentle and high-efficiency hydrothermal approach under reducing conditions for a high-performance asymmetric supercapacitors. The smooth and rounded 3D rGO/Fe 2 O 3-x hydrogel appears to be intact, which possesses extremely light weight and excellent strength. The micromorphology of 3D rGO/Fe 2 O 3-x presents a 3D interconnected macroporous network structure, and the Fe 2 O 3-x nanospheres are distributed on the surface of 3D rGO. The specific capacity of the 3D rGO/Fe 2 O 3-x is up to 273.2 mAh/g. An asymmetric supercapacitor 3D rGO/Fe 2 O 3-x ||3D rGO exhibits an ultrahigh energy density of 114 Wh/kg at a power density of 140 W/kg. Over 20000 cycles, the capacitance retention fading and the coulombic efficiency are 6.18% and ∼100%, respectively. Outstanding supercapacitor performances of the 3D rGO/Fe 2 O 3-x ||3D rGO are attributed to the formation of the V O s in Fe 2 O 3 crystal structure and the distribution of Fe 2 O 3-x nanospheres on the 3D rGO. The 3D rGO/Fe 2 O 3-x displays great potential for utilization as high-performance supercapacitors. [Display omitted] • V O -engineered Fe 2 O 3 on 3D rGO was gained by a gentle hydrothermal approach. • Smooth and rounded 3D rGO/Fe 2 O 3-x hydrogel has 3D interconnected macroporous network. • Electrochemical reaction kinetics and charge storage mechanism were studied. • Asymmetric supercapacitor 3D rGO/Fe 2 O 3-x.||3D rGO shows ultra-high energy density. • Good performance is due to the formation of V O s and the distribution of Fe 2 O 3-x. [ABSTRACT FROM AUTHOR]

In the independent state, PA and GO are too far away from each other to induce any interactions and energy lowering. Accordingly, the energy of the independent state is calibrated to zero as the energy benchmark, signified by pink dotted line. In the combined state, however, PA and GO draw near to form the stable framework PA-GO driven by energy lowering. Structural diagram of PA, GO and PA-GO are presented as inset. [Display omitted] • Phytic acid functionalized graphene oxide (PA-GO) was facilely fabricated. • C 6 H 6 O 24 P 6 12- is the dominant species of phytic acid in PA-GO fabrication system. • Combination mechanism based on electron transfer induced energy lowering for PA-GO. • PA-GO exhibits high adsorption capacity for ionic dyes in five consecutive cycles. Phytic acid functionalized graphene oxide (PA-GO) has encouraging application in environmental treatment. Herein, structure of PA-GO fabricated by hydrothermal method was inspected. Firstly, the aqueous species distribution and ionization states of phytic acid (PA) and graphene oxide (GO) under varying pH was analyzed according to equilibrium thermodynamics to clarify the primary interacting species involved in PA-GO fabrication. Secondly, the hard-soft acid-base (HSAB) theory and spectroscopic characterizations (XPS, FTIR, Raman, UV–Vis and fluorescent spectra) were employed to elucidate the plausible interactions existing in PA-GO. Thermodynamic deduction indicates, C 6 H 6 O 24 P 6 12- is the dominant species of PA, while –OH and –COO- are the dominant state of graphene oxide groups in PA-GO fabrication system. HSAB theory illuminates, the primary interactions occurs between deprotonated oxygen O(O-) and bridged oxygen O(-O-) of phytic acid with hydroxyl group O(Ar-OH) and π electron of graphene oxide. Moreover, electron flows from GO towards PA to induce energy lowering whereby PA-GO is stabilized. HSAB theory prediction was substantiated by spectroscopic analyses. Furthermore, PA-GO efficiently removes ionic dyes in five consecutive cycles with high adsorption capacity. This work may shed light on the fabrication chemistry of PA-GO framework serving as a potential adsorbent. [ABSTRACT FROM AUTHOR]

Abstract: The detailed TEM observations of the immature carbon nanotubes (CNTs), obtained at relatively low temperatures by floating chemical vapor deposition (CVD), indicate that they can be viewed as intermediate objects and record rich and convincible traces about CNT evolution. The results clearly show that the CNT formation in floating CVD follows the particle-wire-tube stepwise evolution mechanism and also provide detailed information about the particle coalescence and structural integration and extension. This new knowledge not only gives a clearer picture for the CNT evolution in floating CVD but also might provide a general method for mechanism studies for other synthesis processes. [Copyright &y& Elsevier]

• Leaf photosynthesis capacity decreases with leaf age and canopy depth. • New leaf expansion results in increase in carbon assimilation for peak growing seasons. • Beer's law is not sufficient for accurate radiation interception modeling. • Accounting for leaf age and canopy structure effects improves GEP estimation. Despite the advances in technologies to derive the maximum rate of Rubisco carboxylation (V c m a x) seasonality at large-scale, factors controlling the temporal dynamics of V c m a x is largely unknown without extensive field measurements at stand scale. In addition, state-of-the-art process-based terrestrial ecosystem models had not accounted the complex canopy structure for estimating radiation interception by vegetation. Both of which could lead to uncertainties in gross ecosystem production (GEP) estimations. Here, we examined the respective and combined effects of leaf age and canopy structure on GEP by integrating the Farquhar photosynthesis model with a two-leaf (sunlit and shaded) canopy radiation interception model based on the Geometric Optical and Radiative Transfer (GORT) theory. We observed that the V c m a x of new leaves was approximately 34.4% higher than that of mature leaves. Considering the seasonal dynamics of V c m a x caused by new leaf expansion, the average bias between the modeled GEP and that derived from the eddy covariance (EC) in the growing season at 8-day temporal scale was reduced from -8% to -1%, with slightly higher correlation (from 0.9 to 0.92) and reduction in root mean squared error (from 6.0 to 3.9 g C m−2 8d−1). Most importantly, the total effect of new leaf expansion and canopy gaps during the growing season was +322 g C m−2 yr−1 and -114 g C m−2 yr−1, which was approximately 22.5% and 8.1% of the total GEP, respectively. Thus, it is important to consider both leaf age and canopy structure when developing a robust terrestrial ecosystem model. We highlighted that V c m a x seasonality and realistic canopy radiation interception simulation are critical for accurate estimation of canopy GEP for evergreen forests. [ABSTRACT FROM AUTHOR]

Scaling natural language processing (NLP) to low-resourced languages to improve machine translation (MT) performance remains enigmatic. This research contributes to the domain on a low-resource English-Twi translation based on filtered synthetic-parallel corpora. It is often perplexing to learn and understand what a good-quality corpus looks like in low-resource conditions, mainly where the target corpus is the only sample text of the parallel language. To improve the MT performance in such low-resource language pairs, we propose to expand the training data by injecting synthetic-parallel corpus obtained by translating a monolingual corpus from the target language based on bootstrapping with different parameter settings. Furthermore, we performed unsupervised measurements on each sentence pair engaging squared Mahalanobis distances, a filtering technique that predicts sentence parallelism. Additionally, we extensively use three different sentence-level similarity metrics after round-trip translation. Experimental results on a diverse amount of available parallel corpus demonstrate that injecting pseudoparallel corpus and extensive filtering with sentence-level similarity metrics significantly improves the original out-of-the-box MT systems for low-resource language pairs. Compared with existing improvements on the same original framework under the same structure, our approach exhibits tremendous developments in BLEU and TER scores. [ABSTRACT FROM AUTHOR]

Chemokine receptors are significantly expressed in the surface of most inflammatory cells and tumor cells. Guided by chemokines, inflammatory cells which express the relevant chemokine receptors migrate to inflammatory lesions and participate in the evolution of inflammation diseases. Similarly, driven by chemokines, immune cells infiltrate into tumor lesions not only induces alterations in the tumor microenvironment, disrupting the efficacy of tumor therapies, but also has the potential to selectively target tumoral cells and diminish tumor progression. Chemokine receptors, which are significantly expressed on the surface of tumor cell membranes, are regulated by chemokines and initiate tumor-associated signaling pathways within tumor cells, playing a complex role in tumor progression. Based on the antagonists targeting chemokine receptors, radionuclide-labeled molecular imaging probes have been developed for the emerging application of molecular imaging in diseases such as tumors and inflammation. The value and limitations of molecular probes in disease imaging are worth reviewing. [Display omitted] • Chemokine receptors are targets for inflammatory disease imaging. • Chemokine receptors are of great value as targets for tumor imaging. • Chemokine receptors can be used as targets for radionuclide therapy for tumors. [ABSTRACT FROM AUTHOR]

• 3D porous graphene with N,S co-doping (NS-3DPG) in KOH-K 2 CO 3 molten salt is proposed. • Asymmetric supercapacitor 3DPG||NS-3DPG shows energy density as high as 33.6 Wh/kg. • In-situ Raman spectra of 3DPG||NS-3DPG was were acquired. • 3DPG||NS-3DPG exhibits little capacitance fading of 1.6 % for 10,000 cycles. • Good properties are ascribed to 3D structure and synergistic effect of N,S co-doping. We prepared a three-dimensional porous graphene (3DPG) with N or/and S doping (N-3DPG, S-3DPG, NS-3DPG) in the KOH-K 2 CO 3 eutectic active molten salt system. Graphene oxide, urea, and 3-mercaptopropionic acid are adopted as the 3DPG, nitrogen, and sulfur precursors, respectively. As a result, a continuous 3D network with dense cross-linked architecture is gained because the KOH-K 2 CO 3 medium works as template to accelerate the conversion of GO to 3D architecture. A specific capacitance of 521 F/g is obtained for the NS-3DPG, which is much larger than that of 3DPG, N-3DPG, S-3DPG. A symmetric supercapacitor NS-3DPG||NS-3DPG delivers an energy density of 21.7 Wh/kg at a power density of 300 W/kg, and displays the capacitance retention ratio of 98.0 % after 10,000 cycles. An asymmetric supercapacitor 3DPG||NS-3DPG is assembled, which shows an energy density as high as 33.6 Wh/kg at a power density of 400 W/kg and little capacitance fading for 10,000 cycles. Outstanding supercapacitor performances of the 3DPG||NS-3DPG are attributed to its excellent 3D hierarchical porous structure and the synergistic effect of N,S co-doping. [Display omitted] [ABSTRACT FROM AUTHOR]

The reduced graphene oxide (rGO)/La(OH) 3 composite is prepared by a simple microwave-assisted synthesis method. The micromorphology of La(OH) 3 is the spindle-like and rod-like architectures through the field emission scanning electron microscope and transmission electron microscope. The obtained rGO/La(OH) 3 displays a maximum specific capacitance of 757 F g−1 at a current density of 0.5 A g−1. An asymmetric supercapacitor of rGO/La(OH) 3 ||rGO is assembled, which exhibits an energy density of 90.5 Wh kg−1 at a power density of 100 W kg−1. In addition, the capacitance retention ratio of the rGO/La(OH) 3 ||rGO reaches 91.8% at a current density of 1 A g−1 after 10,000 charge/discharge cycles. Ultrahigh energy density and a long cycle life are attributed to the rGO which provides conductive substrates, and the anchoring of a thin, homogeneous, and conformal La(OH) 3 layer on the surface of the rGO, which shortens ion transportation paths. The rGO/La(OH) 3 ||rGO is a promising device for supercapacitors. [Display omitted] • The rGO/La(OH) 3 composite is prepared by simple microwave-assisted synthesis. • A thin, homogeneous, and conformal La(OH) 3 layer anchors on the surface of the rGO. • The micromorphology of La(OH) 3 is the spindle-like and rod-like architectures. • The rGO/La(OH) 3 ||rGO exhibits an energy density of 90.5 Wh kg−1. • Capacitance retention ratio of rGO/La(OH) 3 ||rGO reaches 91.8% after 10,000 cycles. [ABSTRACT FROM AUTHOR]

Plant leaf area index (LAI) is an important structural parameter for describing the ability of the canopy to intercept solar radiation, and it plays an important role in the estimation of forest biomass. To overcome the difficulties of current ground measurement instruments in automatically collecting plant LAI, we have designed a continuous LAI measurement system: LAINet. The main part of LAINet includes the distributed Below Node (BN), which is deployed below the canopy and receives transmitted solar radiation, the Above Node (AN), which is used to receive downward radiation above the canopy, and the Central Node (CN), which is used as a data reception and control node. Communication among the nodes is implemented through the Zigbee protocol, while data exchange between the CN and the remote data center server is completed through the General Packet Radio Service (GPRS) network. The design of the LAINet framework and the algorithm for estimating the LAI from a multi-point directional transmittance is presented in this paper. The sensors of LAINet are calibrated on two clear days, and the performance of the proposed system is compared in time series field experiments. Comparison of the nodes’ sensor results indicates that under the condition of the same solar radiation, the response between the different sensors is of high consistence, and each node has a stable calibration coefficient across different dates. In the field coniferous forest experiment, upon comparing with TRAC (Tracing Radiance and Architecture of Canopies) instruments and the results obtained using different data processing algorithms, it is found that the LAINet system can produce the best results with a minimum root mean square error (RMSE = 0.34) and a higher determination coefficient ( R 2 = 0.81). We adopt a multi-day window for aggregating the daily observed LAI to remove the noise that occurs from daily weather variation, and it indicates that the aggregated time series LAI can capture the process of the coniferous needles’ growth and defoliation properly. Thus, it is confirmed that LAINet can be used as a feasible method to conduct automatic ground observations, especially in the scenario where continuous observation is required. [ABSTRACT FROM AUTHOR]

Metal-organic frameworks (MOFs) have recently attracted tremendous attention as membrane materials for desalination owing to their diversified structures, permselectivity, and tunable functionalities. However, the structure-performance relationship of MOF membranes still has not been elucidated. Herein, artificial neural networks (ANN) were developed to form prediction model of MOF thin film nanocomposite (TFN) membrane performances in reverse osmosis applications. Key parameters including MOF size, MOF pore diameter, MOF loading, selective layer thickness, salt concentration, and pressure were collected from literature to predict the water permeability and salt rejection. 5-fold cross-validation and hyperparameter tuning method were employed to acquire a better performing model. When the node structure was 6–9–9–8–2 with the learning rate of 0.001, the developed ANN model attained a remarkable prediction R2 of 90.62%. By introducing mean impact value algorithm into the model, the feature importance of each factor on the membrane performance was also calculated. Rather than the MOF loading and size, proper control of selective layer thickness and MOF pore diameter was key to breaking the permeability-selectivity tradeoff. Finally, ANN proved its ability to predict the membrane performance for water purification and further provide guidance for MOF-based membrane design, or even other TFN membrane design. [Display omitted] • Artificial neural networks are used to optimize and predict MOF TFN membranes. • 5-fold cross-validation and hyperparameter tuning were employed. • R2 of 98.08% and 90.62% were achieved for training and prediction. • MIV algorithm was used for variable screening of the BP neural network. • PA thickness, MOF pore diameter, and MOF sizes were the key factors. [ABSTRACT FROM AUTHOR]

[Display omitted] • Carboxylated g-C 3 N 4 (g-C 3 N 4 -HNO 3) was derived from g-C 3 N 4 treated by 10 M HNO 3. • Carboxyl group played an important role in the process of adsorption and degradation. • The g-C 3 N 4 -HNO 3 exhibited an excellent adsorption property towards MO, LRB and Cr(VI). • The g-C 3 N 4 -HNO 3 showed a good photocatalytic degradation property towards RhB and MB. • The g-C 3 N 4 -HNO 3 could effectively purify the organic and heavy metal wastewater. Graphitic carbon nitride (g-C 3 N 4) was prepared by thermal annealing urea and melamine. And then the carboxylated g-C 3 N 4 (g-C 3 N 4 -HNO 3) was successfully fabricated from the g-C 3 N 4 treated through 10 M nitric acid at 80 °C for 24 h. Several characterization data suggested that g-C 3 N 4 -HNO 3 assembled by 30–190 nm thinner nanosheets possessed lots of carboxyl functional groups, higher specific surface area (88.5173 m2/g) and larger pore volume (0.481684 m3/g). A series of contrast experiments indicated that the g-C 3 N 4 -HNO 3 exhibited an excellent adsorption property towards methyl orange (MO), Lissamine rhodamine B (LRB) and Cr(VI) due to the hydrogen bonding, higher surface area and electrostatic interaction, and a good photocatalytic degradation property towards rhodamine B (RhB) and methylene blue (MB) due to suitable band gap and better electrical conductivity. The g-C 3 N 4 -HNO 3 with excellent adsorption and photocatalytic properties could be used to effectively purify the actual wastewater through adsorption and photodegradation roles. [ABSTRACT FROM AUTHOR]

Abstract: Novel Co3O4 nanoplates and nanobelts were formed on a large scale by a facile and efficient hydrothermal process. The samples were characterized by transmission electron microscopy (TEM), scanning electron microscopy (SEM), X-ray diffraction (XRD). In the same experiment situation, 1D Ni(OH)2 nanowires and ZnO irregular nanoplates were synthesized. The concentration of OH− is important to control the shape of final product. TBAB is the key reactant to form 1D nanostructure. In this report, we demonstrate the fabrication of Co3O4 with various morphologies (plate-, belt-, cube-, urchin-like). The method is a good way to synthesize other 1D metal oxide nanostructures. [Copyright &y& Elsevier]

Abstract: Etherification reaction of hexanol and tert-butyl alcohol in the cyclohexane/dodecylbenzenesulfonic acid (DBSA)/water reverse microemulsion system has been investigated. The effect of several parameters, such as molar ratio of reactants, concentration of DBSA, reaction temperature, ([H2O]/[surfactant]) value and various substrates, on the etherification was also studied. The results showed that the optimal reaction conditions for the etherification were as follows: T =318K, , molar ratio of reactants was 1:1.2 and c DBSA =0.05M. Furthermore, the comparison reactions in several surfactant systems were also performed and the results showed that the conversion in DBSA system was the highest, which proved the key factor affecting the conversion of the reactants was intrinsic nature of DBSA as a Brønsted acid-surfactant-combined catalyst. Finally, the mechanism of reaction was also put forward. After realizing that DBSA is both acid catalyst and surfactant, we concluded that it was dual functions of acid catalyst and surfactant that played an important role in improving reaction rate and conversion of etherification. [Copyright &y& Elsevier]

Objective: The present study investigated the predictive diseases progression value of preoperative fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) in patients with local advanced cervical cancer (LACC)., Methods: In total, 267 patients [median age 58 (range: 27-85) years old] with LACC underwent 18 F-FDG PET/CT prior to any treatment. The maximum standardized uptake values (SUV max ), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) of the primary lesion and metastatic lymph nodes were measured on PET/CT and correlated with clinicopathological features and progression-free survival (PFS)., Results: The median follow-up was 36.52 (range: 3.09-61.29) months. During the observation period, 80 (30.0%) patients exhibited disease progression. Univariate analysis showed that FIGO stage, concurrent chemoradiotherapy (CRT), serum level of carcinoembryonic antigen (CEA) and squamous cell carcinoma antigen (SCC-Ag), primary tumor MTV (pMTV) and TLG (pTLG), lymph nodes SUV max (nSUV max ) and TLG (nTLG), and total metabolic activity (sMTV, sTLG) were associated with PFS. nSUV max  ≥ 5.29, CEA ≥ 7.11 ng/ml and deficiency of concurrent CRT were independent risk factor for PFS (p = 0.006, p = 0.008, p = 0.014). The 3-year PFS for patients with high nSUV max were 42.2% compared to 56.3% for low nSUV max values., Conclusion: Pretreatment cervical and lymph nodes metabolic parameters were associated with PFS in patients with LACC., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

In this paper, the carbon electrode materials were prepared by the KOH-HNO 3 low-temperature activation technique using cheap residual carbon from gasification fine slag (CK) as raw materials. The results showed that the prepared material (CKN-2) which obtained by dry-wet sequential activation at 500°C for 1.5 h at carbon to KOH ratio of 1:2 and further at 80°C for 1 h in 2 mol/L HNO 3 solution. The specific capacitance of CKN-2 reached 142 F/g at a current density of 0.5 A/g. CKN-2 was used to assemble a symmetrical (CKN-2//CKN-2) supercapacitor, which exhibited an energy density of 6.80 Wh/kg at a power density of 244.8 W/kg. The CKN-2//CKN-2 capacitor was tested for stability after 10,000 cycles, with a capacitance retention rate of 97%. These results demonstrate that residual carbon from gasification fine slag can be effectively used to produce high-performance carbon electrode materials for supercapacitors using the KOH-HNO 3 low-temperature sequential co-activation technique., Competing Interests: The authors declare no competing interests., (© 2023 The Authors.)

Mine Internet of Things (MIoT) devices in intelligent mines often face substantial signal attenuation due to challenging operating conditions. The openness of wireless communication also makes it susceptible to smart attackers, such as active eavesdroppers. The attackers can disrupt equipment operations, compromise production safety, and exfiltrate sensitive environmental data. To address these challenges, we propose an intelligent reflecting surface (IRS)-assisted secure transmission system for an MIoT device which enhances the security and reliability of wireless communication in challenging mining environments. We develop a joint optimization problem for the IRS phase shifts and transmit power, with the goal of enhancing legitimate transmission while suppressing eavesdropping. To accommodate time-varying channel conditions, we propose a reinforcement learning (RL)-based IRS-assisted secure transmission scheme that enables MIoT device to optimize both the IRS reflecting coefficients and transmit power for optimal transmission policy in dynamic environments. We adopt the deep deterministic policy gradient (DDPG) algorithm to explore the optimal transmission policy in continuous space. This can reduce the discretization error caused by traditional RL methods. The simulation results indicate that our proposed scheme achieves superior system utility compared with both the IRS-free (IF) scheme and the IRS randomly configured (IRC) scheme. These results demonstrate the effectiveness and practical relevance of our contributions, proving that implementing IRS in MIoT wireless communication can enhance safety, security, and efficiency in the mining industry.

Background: Immunotherapy targeting PD-1/PD-L1 has been proven to be effective for cervical cancer treatment. To explore non-invasive examinations for assessing the PD-L1 status in cervical cancer, we performed a retrospective study to investigate the predictive value of 18 F-FDG PET/CT., Methods: The correlations between PD-L1 expression, clinicopathological characteristics and 18 F-FDG PET/CT metabolic parameters were evaluated in 74 cervical cancer patients. The clinicopathological characteristics included age, histologic type, tumor differentiation, FIGO stage and tumor size. The metabolic parameters included maximum standard uptake (SUVmax), mean standard uptake (SUVmean), total lesion glycolysis (TLG) and tumor metabolic volume (MTV)., Results: In univariate analysis, SUVmax, SUVmean, TLG, tumor size and tumor differentiation were obviously associated with PD-L1 status. SUVmax (rs = 0.42) and SUVmean (rs = 0.40) were moderately positively correlated with the combined positive score (CPS) for PD-L1 in Spearman correlation analysis. The results of multivariable analysis showed that the higher SUVmax (odds ratio = 2.849) and the lower degree of differentiation (Odds Ratio = 0.168), the greater probability of being PD-L1 positive. The ROC curve analysis demonstrated that when the cut-off values of SUVmax, SUVmean and TLG were 10.45, 6.75 and 143.4, respectively, the highest accuracy for predicting PD-L1 expression was 77.0%, 71.6% and 62.2%, respectively. The comprehensive predictive ability of PD-L1 expression, assessed by combining SUVmax with tumor differentiation, showed that the PD-L1-negative rate was 100% in the low probability group, whereas the PD-L1-positive rate was 84.6% in the high probability group. In addition, we also found that the H-score of HIF-1α was moderately positively correlated with PD-L1 CPS (rs = 0.51)., Conclusions: The SUVmax and differentiation of the primary lesion were the optimum predictors for PD-L1 expression in cervical cancer. There was a great potential for 18 F-FDG PET/CT in predicting PD-L1 status and selecting cervical cancer candidates for PD1/PD-L1 immune checkpoint therapy.

In this study, the catalytic effects of desulfurized fly ash (DFA) on the gaseous products of sawdust (SD) pyrolysis were investigated in a tubular furnace. The results indicated that DFA catalyzed the process of SD decomposition to improve the hydrogen content and the calorific value of pyrolysis gas. As to its effect on pyrolysis products, DFA increased the non-oxide content of CH 4 , C 3 H 4 , and H 2 in pyrolysis gas by 1.4-, 1.8-, and 2.3-fold, respectively. Meanwhile, the catalytic effect of DFA reduced the CO and CO 2 yields during DFA/SD pyrolysis. Based on the model compound method, CaSO 3 and Ca(OH) 2 in DFA was proved to have quite different catalytic effects on pyrolysis gas components. Ca(OH) 2 accelerated the formation of CH 4 and H 2 through the cracking of methoxyl during lignin and cellulose degradation, while CaSO 3 favored the generation of CO and CO 2 due to the carbonyl and carboxyl of lignin in SD. CaSO 3 also catalyzed SD pyrolysis to promote the C 3 H 4 yield in pyrolysis gas. Overall, the catalytic pyrolysis of SD with DFA yielded negative-carbon emission, which upgraded the quality of the pyrolysis gas.

Here, we proposed a new strategy to build the integrated graphene cube (Gr) framework@TiO 2 composite to improve the ion transport kinetics and electrical conductivity of TiO 2 as a long-life and high-capacity anode for lithium ion batteries. Combined with the salt template method for ultra-thin framework, the distinct structure of Gr@TiO 2 shows an excellent electrochemical performance, e.g., initial coulombic efficiency (ICE), rate performance and specific capacity, due to the increased kinetics of lithium ions. Through this method, the integrity is dramatically improved and the pulverization and agglomeration of the anode after long-term cycles are restrained. The optimized Gr@TiO 2 displays a high stable reversible capacity of 179.5 mAh g -1 after 4000 cycles at 1 A g -1 , excellent rate performance (125.5 mAh g -1 at 5 A g -1 ). Kinetic studies through Electrochemical Impedance Spectra, Galvanostatic Intermittent Titration Technique and Linear Sweep Voltammetry confirm that the electrical conductivity and ion transport kinetics are dramatically improved through the ultra-thin graphene cube framework as a heterojunction structure of Gr@TiO 2 ., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Inc. All rights reserved.)

The COVID-19 pandemic has generated a new era in the world, also in the food safety. Up to now, there is no evidence to suggest that people can infect COVID-19 via food contaminated by SARS-CoV-2. Here, we analyzed the results of regular SARS-CoV-2 nucleic acid testing of considerable cold-chain food practitioners, cold-chain food surfaces, and their internal or external packaging as well as their associated environments, aiming to explore the risk of cold-chain food being contaminated by SARS-CoV-2 and the probability of people infecting COVID-19 through contaminated cold-chain food in the context of COVID-19 epidemic. This study found that only two batches of cold-chain food were contaminated by SARS-CoV-2, none of the cold-chain food handler were infected due to effective regulatory measures for cold-chain food. Therefore, effective supervision and preventive methods could effectively reduce the transmission risk of SARS-CoV-2 on cold-chain food., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Water pollution threatens the safety of human production and life. To quickly respond to water pollution, it is important for water management staff to predict water quality changes in advance. Drawing on the temporality of water quality data, the leaky integrator echo state network (ESN) was introduced to construct the water quality prediction models for dissolved oxygen (DO), permanganate index (CODMn), and total phosphorus (TP), respectively. First, the missing values were filled by the linear trend method of adjacent points, and the outliers were detected and corrected by the Z -score method and the linear trend method. Second, the singular spectrum analysis (SSA) was performed to denoise the original monitoring data, such that the predicted data catch up with the real data, and the model accuracy is not affected by the hidden noise in the data. Third, the correlation between water quality indices was measured by the maximum information coefficient (MIC), and the strongly correlated indices were imported to the prediction model. Finally, according to these strong correlation indicators, the water quality prediction models based on multiple features were constructed, respectively, using the offline and online learning algorithms of the ESN. The hyperparameters of the models were optimized through the sequential model-based optimization (SMBO). Experimental results show that the proposed water quality prediction models, namely, SSA-MIC-SMBO-Offline ESN and SSA-MIC-SMBO-Online ESN, predicted DO, CODMn, and TP accurately, providing suitable tools for practical applications., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2022 Yan Kang et al.)

Purpose: Identification of microsatellite instability high (MSI-H) colorectal cancer (CRC) is crucial for screening patients most likely to benefit from immunotherapy. We aim to investigate whether the metabolic characteristics is related to MSI status and can be used to predict the MSI-H CRC., Methods: A retrospective analysis was conducted on 420 CRC patients who were identified via [ 18 F]fluorodeoxyglucose ( 18 F-FDG) positron emission tomography (PET)/computed tomography(CT) prior to therapy. Maximum standardized uptake (SUV max ), mean standardized uptake (SUV mean ), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) of the primary tumor were calculated and compared between MSI-H and microsatellite stability (MSS). Predictive factors of MSI status were selected from metabolic parameters and clinicopathological profiles via a multivariate analysis., Results: Of 420 colorectal cancers, 44 exhibited a high incidence of MSI. Both MTV and TLG were significantly higher in MSI-H group compared with the MSS group (P = 0.004 and P = 0.010, respectively). Logistic regression analysis indicated that CRC with MSI-H were related to younger age (P = 0.013), primary lesion located at right hemi-colon (P < 0.001) and larger MTV on PET/CT imaging (P = 0.019). MTV more than 32.19 of colorectal cancer was linked to the presence of MSI (P = 0.019)., Conclusion: Tumor metabolic burden were higher in MSI-H CRC which may be useful for predicting the MSI status of CRC patient and thus aid in determination of immunotherapy for patients with CRC., (© 2022. The Author(s).)

This study aimed to establish a self-corrective machine learning model base on co-pyrolysis data of biomass and coal. Proximate and ultimate analysis of raw materials were chosen as input parameters. Radial basis function (RBF), support vector machine (SVM), and random forest (RF) were used to build the base regression models for the fusion (FU) model. 96 sets of the experimental data were applied to train and test the base models. A learning weight were then determined by the predicted performance of base models. Based on the learning weight method, FU model spontaneously regulated and controlled the weight of base models to output the predicted result of co-pyrolysis products. The coefficient of determination (R 2 ) was more than 0.99 and the root-mean-squared error (RMSE) was lower than 0.88%. The results suggested that FU model was more accurately adequate to forecast the yields of co-pyrolysis products than any of the base models., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

As one of the fast evolution of remote sensing and spectral imagery techniques, hyperspectral image (HSI) classification has attracted considerable attention in various fields, including land survey, resource monitoring, and among others. Nonetheless, due to a lack of distinctiveness in the hyperspectral pixels of separate classes, there is a recurrent inseparability obstacle in the primary space. Additionally, an open challenge stems from examining efficient techniques that can speedily classify and interpret the spectral-spatial data bands within a more precise computational time. Hence, in this work, we propose a 3D-2D convolutional neural network and transfer learning model where the early layers of the model exploit 3D convolutions to modeling spectral-spatial information. On top of it are 2D convolutional layers to handle semantic abstraction mainly. Toward simplicity and a highly modularized network for image classification, we leverage the ResNeXt-50 block for our model. Furthermore, improving the separability among classes and balance of the interclass and intraclass criteria, we engaged principal component analysis (PCA) for the best orthogonal vectors for representing information from HSIs before feeding to the network. The experimental result shows that our model can efficiently improve the hyperspectral imagery classification, including an instantaneous representation of the spectral-spatial information. Our model evaluation on five publicly available hyperspectral datasets, Indian Pines (IP), Pavia University Scene (PU), Salinas Scene (SA), Botswana (BS), and Kennedy Space Center (KSC), was performed with a high classification accuracy of 99.85%, 99.98%, 100%, 99.82%, and 99.71%, respectively. Quantitative results demonstrated that it outperformed several state-of-the-arts (SOTA), deep neural network-based approaches, and standard classifiers. Thus, it has provided more insight into hyperspectral image classification., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2021 Douglas Omwenga Nyabuga et al.)

Objective: The aim of this study was to evaluate PET/FDG metabolic parameters in locally advanced GEJC and correlate it with molecular pathological profiles., Methods: We retrospectively analyzed data from 66 patients with a histopathological diagnosis of GEJC who had undergone 18 F-FDG PET/CT before surgical resection. Maximum standardized uptake (SUV max ), mean standardized uptake (SUV mean ), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) of the primary tumor were measured and calculated using the region of interest (ROI) technique. The relationship between metabolic parameters and the Lauren's classification, histologic differentiation, Ki-67 staining and positivity for human epidermal growth factor receptor 2 (HER2), c-Met, and epidermal growth factor receptor (EGFR) were investigated through immunohistochemical (IHC) analyses., Results: Of the total 66 patients, significant differences were observed between intestinal and non-intestinal (mixed and diffuse) adenocarcinomas in SUV max (8.23 ± 2.83 vs. 6.29 ± 2.41, P = 0.008), SUV mean (4.85 ± 1.47 vs. 3.93 ± 1.22, P = 0.017), MTV (24.96 cm 3 vs. 8.90 cm 3 ; P = 0.004), and TLG (97.38 cm 3 vs. 37.09 cm 3 , P = 0.005) values. SUV max , MTV, and TLG of moderately differentiated adenocarcinomas were significantly higher than those of the poorly differentiated ones. SUV max was significantly higher in tissues with a higher Ki-67 index or in the c-MET-negative group (P = 0.045, P = 0.036). No significant correlation was found between metabolic parameters and the expression of HER2 or EGFR in GEJC., Conclusion: 18 F-FDG PET/CT may be useful for predicting the molecular pathological profiles of GEJC and for determining appropriate therapeutic strategy.

Objective: The present study investigated the prognosis value of preoperative fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) in patients with local advanced gastric cancer (LAGC)., Methods: In total, 144 patients [median age 63 (range: 48-80) years old] with LAGC underwent 18 F-FDG PET/CT prior to any treatment. The maximum standardized uptake values (SUV max ), mean standardized uptake values (SUV mean ), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) of the primary lesion were measured on PET/CT and correlated with clinicopathological features and survival., Results: Significant differences in SUV mean , SUV max , MTV and TLG were found according to Lauren's classification, histologic grade and T category (P<0.05). During the 26.5-month follow-up, 51 (35.4%) patients died and 70 (48.6%) exhibited disease progression. The optimal thresholds of MTV and TLG were 15.1 cm 3 and 47.3 cm 3 , respectively. The 3-year progression-free survival (PFS) and overall survival (OS) for patients with high TLG values were 30% and 38% compared to 38% and 47% for low TLG values, respectively (P<0.05). Univariate and multifactor analyses demonstrated that lymph node metastasis and T stage were independent prognostic factors for PFS; T stage, histologic grade and TLG were independent prognostic factors for OS (P<0.05). Molecular markers had no relationship with patient's outcomes., Conclusions: Metabolic activity of primary gastric tumors from 18 F-FDG PET/CT is a prognostic factor in patients with LAGC., (Copyright © 2019 Chinese Journal of Cancer Research. All rights reserved.)

CeO 2 nanorods anchored on mesoporous carbon exhibit high activity and stability in aerobic oxidative coupling of alcohols and amines to imines. The abundant surface Ce 3+ and the suitable interaction between CeO 2 nanorods and the carbon support should be responsible for the excellent catalytic behaviors.