Search

Semiconductor materials have become a competitive candidate for surface-enhanced Raman scattering (SERS) substrate. However, powdered semiconductors are difficult to execute a fast in situ detection for trace analytes. Here, we developed a new flexible semiconductor SERS substrate by in situ densely growing anatase TiO2 nanoparticles on the surface of cotton fabric through a filtration-hydrothermal method, in which TiO2 exhibits excellent controllability in size and distribution by regulating the ratio of water to alcohol in synthesis and the number of filtration-hydrothermal repetitive cycle. Cotton fabric/TiO2 (Cot/TiO2) substrate exhibits a high SERS activity and excellent spectral repeatability. The developed substrate has an ultra-high stability that can withstand long-term preservation; it can even resist the corrosions of strong acid and alkali, as well as high temperature up to 100 °C and low temperature down to − 20 °C. The flexible substrate can be used to carry out a rapid in situ detection for quinolone antibiotic (enrofloxacin and enoxacin) residues on the fish body surface by using a simple swabbing method, with high quantitative detection potential (up to an order of magnitude of 10−7 M), and even for the simultaneous detection of both drug residues. The flexible substrate also exhibits an excellent recyclability up to 6 recycles in the actual SERS detection. [ABSTRACT FROM AUTHOR]

High winds are a type of catastrophic weather characterized by wind speeds over 10.8 m·s−1, occurring in all seasons, and have become more frequent, impacting crop growth, agricultural production and quality of life. It is crucial to understand the spatial and temporal distribution patterns of high winds, as well as their speed and other characteristics, for logical planning of agricultural production and the creation of disaster resilience measures. This study applied the climate tendency, accumulative anomalies, theory of run, Mann–Kendall trend and Theil–Sen median to analyse the spatial and temporal distribution characteristics of the average wind speed and high wind days in Jilin Province, the probability of occurrence of high winds of various magnitudes in different eras, and the gale concentration degree (GCD) throughout Jilin Province for a total of 40 years from 1982 to 2021. The average wind speed and number of high wind days in Jilin Province have decreased over the past 40 years, and this trend has slowed over time. The average GCD in Jilin Province has shown an increasing trend over the last 40 years, with the average GCD being highest in Liouhe and lowest in Linjiang. In general, level six high winds were the main wind hazard level in Jilin Province, with the highest frequency occurring in different seasons and decades. In addition, the occurrence of high wind days is affected by global climate change and different underlying surfaces, which leads to maize and yield reduction. Research on the spatiotemporal distribution of high winds can provide important suggestions for the prevention and management of high wind disasters. [ABSTRACT FROM AUTHOR]

As the climate warms, the impact of drought on plants has increased. We aimed to construct a comprehensive drought index (CDI), coupling soil-vegetation-atmosphere drought and heat conditions based on multi-source information, and to combine it with static and dynamic drought hazard evaluation models to analyze the spatial and temporal distribution characteristics of agricultural drought disasters and hazards during the growing season (May to September) in Northeast China (NEC). The results demonstrated that the CDI could combine the benefits of meteorology (standardized precipitation evapotranspiration index, SPEI), vegetation (vegetation health index, VHI), and soil (standardized soil moisture condition index, SMCI) indices. This was performed using a relative weighting method based on the remote sensing data of solar-induced chlorophyll fluorescence (SIF) to determine the weights of SPEI, VHI, and SMCI. The CDI for drought monitoring has the advantages of broad spatial range, long time range, and high accuracy, and can effectively reflect agricultural drought; the growing season in NEC showed a trend of becoming drier during 1982–2020. However, the trends of the drought index, the impact range of drought events, and the hazard of agricultural drought all turned around 2000. The drought hazard was highly significant (p < 0.001) and decreased from 2000 to 2020. The frequency of drought disasters was the highest, and the hazard was the greatest in May. The best level of climatic yield anomalies in maize were explained by drought hazard in August (R2 = 0.28). In the center and western portions of the study area, farmland and grassland areas were where higher levels of hazard were most commonly seen. The dynamic hazard index is significantly correlated with climatic yield anomalies and can reflect the actual impact of drought on crop yield. The study results serve as a scientific foundation for drought risk assessment and management, agricultural planning, and the formulation of drought adaptation policies, as well as for ensuring food security in China. [ABSTRACT FROM AUTHOR]

• Rice cultivation areas continue to expand from tropical and subtropical areas to high altitudes and high latitudes, and the chances of rice suffering from chilling injury gradually increase. • Regional-scale chlorophyll fluorescence data show a close correlation with the monitoring chilling injury losses in rice. • Real-time hazard assessment of the occurrence of chilling injury in rice and its intensity, and estimation of the possible loss of rice yield caused by different disaster-causing intensities. Rice is a warm-temperature crop, and sterile-type chilling injuries may be induced by acute periods of low-temperature weather during the reproductive growth period. This study considered the daily mean and minimum temperatures in Northeast China from 1979 to 2018 as influencing factors to construct a process-based rice accumulated intensity index (PARII) and hazard assessment model based on known crop disaster periods, analyzed the spatiotemporal distribution characteristics of chilling injury during the rice growth period (booting and flowering stages), used solar-induced chlorophyll fluorescence (SIF) and yield fluctuation data to calculate the adaptability of the hazard assessment model, and selected two typical events of disaster processes to verify the proposed real-time hazard assessment model. The change in the cumulative intensity index of rice sterile-type chilling injury indicated an increasing trend in chilling injury in the rice booting stage. Based on the probability density static hazard and cumulative probability dynamics, the results of real-time hazard analysis showed that the chilling injury hazard area was significantly expanded compared with the sterile-type chilling injury during the booting and flowering periods. The hazard value was greater than 0.2 in central and southeastern Heilongjiang, and the static hazard index was significantly negatively correlated with SIF and fluctuating yield, which indicated the chilling injury impacted rice yield and physiology. Regional-scale hazard levels were assessed by daily real-time hazard evaluation to highlight spatial heterogeneity in crop stress and damage. The results of this study provide a scientific basis for real-time risk assessment and management of chilling injury in rice crops and may support future adaptation strategies for addressing risks associated with severe low-temperature events. [Display omitted] [ABSTRACT FROM AUTHOR]

The climate changes influence the growing suitability of peanut, an important oil crop. Climatic suitability evaluation in the Huang-Huai-Hai region, the main peanut producing region of China, which can optimize peanut planting structure and provide basis for increasing output. In this study, the temperature, precipitation, sunshine and comprehensive suitability models were established by using the climatic suitability function in different growth periods of peanut. In this study, the climate suitability function of peanut in different growth periods was used to establish the temperature, precipitation, sunshine and comprehensive suitability model. Combined with the meteorological data after Anusplin interpolation, the spatial distribution and chronological change of peanut climate suitability were analyzed. The results show that with climate change, the overall climate becomes warmer and drier and the temperature and precipitation suitability increase, but the sunshine suitability decreases. Based on the comprehensive suitability model, the suitability evaluation results are divided into four levels: the most suitable, suitable, sub-suitable and unsuitable. Among them, the most suitable peanut planting areas in the Huang-Huai-Hai region are concentrated in the west of the Haihe River Basin and the Huaihe River Basin. The data from the next 30 years show that both the most suitable and suitable areas have been expanded. Through the verification of yield correlation analysis and spatial distribution of disaster frequency, it can be seen that the evaluation results have high accuracy, which can be used to guide and optimize peanut production practices. [ABSTRACT FROM AUTHOR]

In recent years, global warming has led to frequent waterlogging disaster (WLD), hindering the normal growth and development of crops, affecting the sustainable development of the peanut industry and food security in China. Henan Province, the main peanut-producing area with frequent WLD, was selected as the study area. Based on the soil-crop-atmosphere continuum system, this study constructed a comprehensive waterlogging index (CWI) to monitor waterlogging events. To determine the applicability of CWI, the standardized precipitation evapotranspiration index (SPEI) was calculated. A risk assessment model was constructed to evaluate the hazards of WLD during the different stages of development of spring peanut. The water stress at different growth stages of peanut on crucial physiological indices were studied to determine the natural vulnerability curve of WLD. As a consequence, based on the "Four-Factor" theory of disaster formation, this study established a dynamic WLD assessment model for peanut and evaluated the comprehensive risk of WLD in Henan from 1990 to 2020. The results indicated that the CWI is capable of accurately identifying waterlogging events and peanut responded significantly differently to water stress; the longer the duration of stress in the late growth period (LGP), the higher was the rate of yield reduction. The comprehensive risk of WLD to peanut rose from north to south during the three growth periods. During the LGP, high-risk regions constituted approximately 34.3% of the total population. This study provides a scientific basis and technical support for better exploration of peanut growth under waterlogging stress to manage and reduce the risk of WLD. • The comprehensive waterlogging index (CWI) can be used to identify waterlogging events. • Different water stress days in three periods had different effects on the growth of spring peanut. • Water stress in the late growth period had the greatest influence on the yield of spring peanut. • The risk was evaluated through "Four-Factor" theory, while the south of Henan had high-risk levels. [ABSTRACT FROM AUTHOR]

Due to the national nutrition crisis and the adjustment of planting structure, millet has once again become a widely planted cash crop in Northern China. However, as the climate warms in recent years, drought has occurred frequently and repeatedly in Northern China, which has seriously threatened millet production safety in this area. Therefore, it is urgent to clarify the hazard of millet drought disaster and provide reference for the formulation of millet disaster prevention and reduction measures. In this paper, combined with the water demand of millet in each growth period, Standardized Precipitation Requirement Index (SPRI) was selected to identify and quantify the drought disaster of millet. Considering the impact of different degrees of drought in different growth periods, a hazard assessment model is constructed to evaluate the hazard of millet drought disaster in Northern China under the background of climate change. The results show that: (1) SPRI can well characterize the drought of millet in Northern China. (2) In the context of climate change, millet drought in Northern China shows a trend of increasing intensity and decreasing frequency, and it is possible that millet drought will be even more severe in the future. (3) Combined with the hazard assessment model, millet drought in Northern China will still be dominated by middle hazard in the future, but the areas with high hazard will gradually increase, mainly distributed in northeast China, central and western Inner Mongolia and northern Gansu. The research results can be of great practical significance for the adjustment of agricultural production structure in the future, especially for the sustainable development of agriculture and the formulation of measures to prevent and resist agricultural disasters. [Display omitted] • We apply SPRI to identify millet drought by considering actual water demand. • Future changes of millet drought evaluated by CMIP6-GCM models. • Hazard assessment model was presented combined with disaster loss coefficient. • The areas with high hazard of millet drought will gradually increase in future. [ABSTRACT FROM AUTHOR]

Landslides pose a constant threat to the lives and property of mountain people and may also cause geomorphological destruction such as soil and water loss, vegetation destruction, and land cover change. Landslide susceptibility assessment (LSA) is a key component of landslide risk evaluation. There are many related studies, but few analyses and comparisons of models for optimization. This paper aims to introduce the Tree-structured Parzen Estimator (TPE) algorithm for hyperparameter optimization of three typical neural network models for LSA in Shuicheng County, China, as an example, and to compare the differences of predictive ability among the models in order to achieve higher application performance. First, 17 influencing factors of landslide multiple data sources were selected for spatial prediction, hybrid ensemble oversampling and undersampling techniques were used to address the imbalanced sample and small sample size problem, and the samples were randomly divided into a training set and validation set. Second, deep neural network (DNN), recurrent neural network (RNN), and convolutional neural network (CNN) models were adopted to predict the regional landslides susceptibility, and the TPE algorithm was used to optimize the hyperparameters respectively to improve the assessment capacity. Finally, to compare the differences and optimization effects of these models, several objective measures were applied for validation. The results show that the high-susceptibility regions mostly distributed in bands along fault zones, where the lithology is mostly claystone, sandstone, and basalt. The DNN, RNN, and CNN models all perform well in LSA, especially the RNN model. The TPE optimization significantly improves the accuracy of the DNN and CNN (3.92% and 1.52%, respectively), but does not improve the performance of the RNN. In summary, our proposed RNN model and TPE-optimized DNN and CNN model have robust predictive capability for landslide susceptibility in the study area and can also be applied to other areas containing similar geological conditions. [ABSTRACT FROM AUTHOR]

Agricultural drought is a major problem facing China's agricultural production. In this study, the cash crop 'peanut' was used as an example to explore vulnerability. Through the atmosphere–plant–soil continuum system, a single index that could represent different types of droughts affecting peanuts was selected and weighted using the CRITIC weighting method to construct a multi-source data fusion drought index (MFDI). Then, Pearson correlation analysis between the comprehensive drought index and relative meteorological yield and the Mann–Kendall trend test for different growth periods of peanuts were used to verify MFDI and analyze the variation over time. A three-dimensional vulnerability assessment method of drought intensity–drought duration–yield reduction rate was established based on the run theory and trend surface analysis. The results show that the constructed multi-source data fusion drought index (MFDI) can more accurately characterize the actual drought conditions of peanuts in Shandong Province. The MFDI results showed that the drought severity in the coastal areas of the study area decreased with the growth and development of peanuts, while the drought became more severe in the western and northern parts during the late growth period of peanuts. The vulnerability surface of the drought intensity–drought duration–yield reduction rate showed that when the drought intensity was < 0.8 and the duration was < 3.5 months, the vulnerability of peanut crops was low, and then with the increase in drought intensity or duration, the vulnerability increased. The impact of drought duration cannot be ignored. In contrast to traditional vulnerability assessment methods, this study established a three-dimensional vulnerability surface, which provides a new approach for agricultural drought vulnerability assessment. The research results are helpful for a deeper understanding of the relationship between drought and crop vulnerability and provide scientific support for local governments in formulating disaster prevention and mitigation policies. [ABSTRACT FROM AUTHOR]

In this paper, we investigate photonic nanojets (PNJs) generated from silicon-based cuboids and grating structures. The cuboid structure consists of a base microcuboid and a nanocuboid sitting on top. By tuning the parameters of cuboids and surrounding medium, we show that ultra-narrow PNJs with spot sizes between 82 nm (~ λ /7.8) and 86 nm (~ λ /7.4) can be achieved under a 638 nm TE-polarized light illumination. These results are comparable to the solid immersion resolution limit of λ /7.8 for silicon lenses, but significantly exceeding the half wavelength limit in air. By arranging an array of hybrid-cuboids structures into a grating structure, we show that the PNJ resolution can be pushed beyond the solid immersion limit, reaching λ /8.3 with spot size ~77 nm. This is one of the highest optical resolutions reported to date for a visible light PNJ array generated by a grating and may find applications in sensing and lithography. [ABSTRACT FROM AUTHOR]

The development of soft electronics and soft fiber devices has significantly advanced flexible and wearable technology. However, they still face the risk of damage when exposed to sharp objects in real‐life applications. Taking inspiration from nature, self‐healable materials that can restore their physical properties after external damage offer a solution to this problem. Nevertheless, large‐scale production of self‐healable fibers is currently constrained. To address this limitation, this study leverages the thermal drawing technique to create elastic and stretchable self‐healable thermoplastic polyurethane (STPU) fibers, enabling cost‐effective mass production of such functional fibers. Furthermore, despite substantial research into the mechanisms of self‐healable materials, quantifying their healing speed and time poses a persistent challenge. Thus, transmission spectra are employed as a monitoring tool to observe the real‐time self‐healing process, facilitating an in‐depth investigation into the healing kinetics and efficiency. The versatility of the fabricated self‐healable fiber extends to its ability to be doped with a wide range of functional materials, including dye molecules and magnetic microparticles, which enables modular assembly to develop distributed strain sensors and soft actuators. These achievements highlight the potential applications of self‐healable fibers that seamlessly integrate with daily lives and open up new possibilities in various industries. [ABSTRACT FROM AUTHOR]

As the population ages, the worldwide prevalence of Alzheimer's disease (AD) as the most common dementia in the elderly is increasing dramatically. However, a long‐term challenge is to achieve rapid and accurate early diagnosis of AD by detecting hallmarks such as amyloid beta (Aβ42). Here, a multi‐channel microfluidic‐based plasmonic fiber‐optic biosensing platform is established for simultaneous detection and differentiation of multiple AD biomarkers. The platform is based on a gold‐coated, highly‐tilted fiber Bragg grating (TFBG) and a custom‐developed microfluidics. TFBG excites a high‐density, narrow‐cladding‐mode spectral comb that overlaps with the broad absorption of surface plasmons for high‐precision interrogation, enabling ultrasensitive monitoring of analytes. In situ detection and in‐parallel discrimination of different forms of Aβ42 in cerebrospinal fluid (CSF) are successfully demonstrated with a detection of limit in the range of ≈30–170 pg mL−1, which is one order of magnitude below the clinical cut‐off level in AD onset, providing high detection sensitivity for early diagnosis of AD. The integration of the TFBG sensor with multi‐channel microfluidics enables simultaneous detection of multiple biomarkers using sub‐µL sample volumes, as well as combining initial binding rate and real‐time response time to differentiate between multiple biomarkers in terms of binding kinetics. With the advantages of multi‐parameter, low consumption, and highly sensitive detection, the sensor represents an urgently needed potentials for large‐scale diagnosis of diseases at early stage. [ABSTRACT FROM AUTHOR]

Nanoscale high-intensity illuminations can be produced by dielectric microspheres, which are used for super-resolution imaging and optical nonlinear enhancement. Herein, a microscale chromatic dispersion assisted of a microsphere is experimentally presented. We find that a micro-iridescent focus can be generated from a microsphere put on a reflective nanograting under an oblique white-light illumination. The size of the micro-iridescent focus is smaller than the diameter of the microsphere, and the long wavelengths of light contributing to the micro-iridescent focus are distributed farther away from the microsphere. Furthermore, a curved-iridescent focus can also be obtained. Finally, it shows that the direction of the micro-iridescent focus is perpendicular to that of the reflective nanograting and the role of oblique illumination in experiments is discussed numerically. Our works present that a microsphere on a reflective nanograting can produce a microscale chromatic dispersion. This novel structure may have potential applications in the miniaturization of optical spectrometers. [ABSTRACT FROM AUTHOR]

Background: Lipoprotein lipase (LPL) is the key enzyme responsible for the hydrolysis of triglycerides. Loss-of-function variants in the LPL gene are associated with hypertriglyceridemia (HTG) and HTG-related diseases. Unlike nonsense, frameshift and canonical GT-AG splice site variants, a pathogenic role for clinically identified LPL missense variants should generally be confirmed by functional analysis. Herein, we describe the clinical and functional analysis of a rare LPL missense variant. Methods: Chinese patients with HTG-associated acute pancreatitis (HTG-AP) were screened for rare nonsense, frameshift, missense or canonical GT-AG splice site variants in LPL and four other lipid metabolism-related genes (APOC2, APOA5, GPIHBP1 and LMF1) by Sanger sequencing. The functional consequences of the LPL missense variant of interest were characterized by in vitro expression in HEK-293T and COS-7 cells followed by Western blot and LPL activity assays. Results: Five unrelated HTG-AP patients were found to be heterozygous for a rare East Asian-specific LPL missense variant, c.862G > A (p.Ala288Thr). All five patients were adult males, and all were overweight and had a long history of alcohol consumption. Transfection of LPL wild-type and c.862G > A expression vectors into two cell lines followed by Western blot analysis served to exclude the possibility that the p.Ala288Thr missense variant either impaired protein synthesis or increased protein degradation. Contrary to a previous functional study that claimed that p.Ala288Thr had a severe impact on LPL function (reportedly having 36% normal activity), our experiments consistently demonstrated that the variant had a comparatively mild effect on LPL functional activity, which was mediated through its impact upon LPL protein secretion (~ 20% reduced secretion compared to wild-type). Conclusions: In this study, we identified the East Asian-specific LPL c.862G > A (p.Ala288Thr) missense variant in five unrelated HTG-AP patients. We demonstrated that this variant exerted only a relatively mild effect on LPL function in two cell lines. Heterozygosity for this LPL variant may have combined with alcohol consumption to trigger HTG-AP in these patients. [ABSTRACT FROM AUTHOR]

Maize is susceptible to drought and low temperatures. In recent years, drought, low temperatures, and their composite events have often occurred during the growth period of maize, causing a huge impact. In this study, maize in the Songliao Plain was used as the research object. Based on the crop water surplus deficit index (CWSDI) and heat index (F(T)), combined with the Theil–Sen median and Mann–Kendall tests (Sen–MK) and empirical orthogonal function (EOF), the temporal trends and spatial patterns of drought and low temperatures in different growth periods of maize were obtained. Copula modelling was used to analyse the joint probability distribution and return period of drought and low temperatures. The results showed that the temporal variation trend of the CWSDI was significantly different at different growth periods of maize, and there were different trends and spatial modal distributions. However, the temporal variation trend of F(T) was similar, showing a downward trend over the entire region. There was no obvious asymmetry or skew‐dependent structure in the distribution of concurrent events of drought and low temperature; however, the joint probability contours of different growth periods were biased to the upper left. The recurrence period of drought and low‐temperature concurrent events was within 2 years, and the recurrence period was basically between 2 and 5 years, with a reduction in drought or low temperatures. [ABSTRACT FROM AUTHOR]

Accurate measurement of the junction temperature Tj is crucial for ensuring safe operation and evaluating the performance of silicon carbide (SiC) metal–oxide–semiconductor field-effect transistors (MOSFETs). In this paper, the junction temperature of a half-bridge is monitored by combining transient voltage and current peaks across the lower device. Both theoretical analysis and switch tests validate that the peak induced voltage and peak reversed current during the commutation transient exhibit a linear relationship with the temperature of the corresponding devices. The impact of load current and bus voltage on the measurement results is also investigated. Moreover, the effectiveness of the proposed method is confirmed by carrying out tests at different temperatures, and the feasibility of online implementation is discussed. The experimental results show that the proposed method has high linearity and sensitivity and can simultaneously provide temperature information for both devices of a half-bridge. [ABSTRACT FROM AUTHOR]

Inspired by nature, various self‐healing materials that can recover their physical properties after external damage have been developed. Recently, self‐healing materials have been widely used in electronic devices for improving durability and protecting the devices from failure during operation. Moreover, self‐healing materials can integrate many other intriguing properties of biological systems, such as stretchability, mechanical toughness, adhesion, and structural coloration, providing additional fascinating experiences. All of these inspirations have attracted extensive research on bioinspired self‐healing soft electronics. This review presents a detailed discussion on bioinspired self‐healing soft electronics. Firstly, two main healing mechanisms are introduced. Then, four categories of self‐healing materials in soft electronics, including insulators, semiconductors, electronic conductors, and ionic conductors, are reviewed, and their functions, working principles, and applications are summarized. Finally, human‐inspired self‐healing materials and animal‐inspired self‐healing materials as well as their applications, such as organic field‐effect transistors (OFETs), pressure sensors, strain sensors, chemical sensors, triboelectric nanogenerators (TENGs), and soft actuators, are introduced. This cutting‐edge and promising field is believed to stimulate more excellent cross‐discipline works in material science, flexible electronics, and novel sensors, accelerating the development of applications in human motion monitoring, environmental sensing, information transmission, etc. [ABSTRACT FROM AUTHOR]

Electroadhesion devices render shape perception on the flat surface by reconstructing friction based on the finger position. The positioning sensor with a low sampling rate limits rendering because of the discontinuous friction caused by fast finger sliding. The positioning sensor with a higher sampling rate needs to be designed to meet the high-fidelity rendering at fast movement. However, a sensor with a high sampling rate that exceeds the range of human perception is also unnecessary because this will increase the burden of the hardware and software. Thus, it is importance to determine the upper limit of the sampling rate required for electroadhesion devices. The minimum perceived width and sliding velocity together determine the maximum sampling rate. This paper uses the line with varying widths to study the minimum perceived linewidth. The minimum perceived linewidths and influencing factors were studied by psychophysical experiments under 16 conditions of four driving voltages and four sliding velocities. The results showed that minimum perceived linewidths were in the micron scale, and the averages were 5.00–53.75 μ m. The minimum perceived linewidths were significantly affected by voltages and velocities, especially at low voltages and fast velocities. The minimum perceived width and influencing factors guide the future electroadhesion application. • We proposed a design to maintain finger moving velocity constant and obtain 10 μ m smallest linewidth with four different velocities. • We measured minimum perceived linewidths by electroadhesion for the first time and determined dual effects of driving voltage and moving velocity. • We found that the averages of minimum perceived linewidths increased with increasing velocities at low voltages. [ABSTRACT FROM AUTHOR]

Magnetic biochar adsorbents often suffer from the uneven distribution and shedding problems of nanoparticles. In this study, a one-pot sol-gel pyrolysis method was proposed to synthesize a MnFe 2 O 4 functionalized magnetic sawdust-based biochar (MnFe 2 O 4 @SBC) for efficient removal of diclofenac sodium (DCF). The MnFe 2 O 4 @SBC was characterized by XRD, Raman, VSM, TG-DSC, SEM, TEM, BET, FTIR and XPS. The results demonstrated that the combination of sol-gel and sawdust effectively led to a homogeneous distribution of MnFe 2 O 4 on biochar and the MnFe 2 O 4 @SBC possessed a much richer pore structure and functional groups than the original biochar. A systematic comparison of MnFe 2 O 4 @SBC with commercial activated carbon (CAC) was conducted by analyzing the effects of initial pH, adsorbent dosage, coexisting ions, contact time and temperature on their adsorption performance. Based on the adsorption isotherm study, the maximum adsorption capacity of MnFe 2 O 4 @SBC was predicted to be 352.17 mg/g, which was almost 3.5 times that of CAC. Selectivity adsorption study and real water-based removal experiment further demonstrated the satisfactory adsorption selectivity and applicability of MnFe 2 O 4 @SBC for DCF. This study reveals that the one-pot sol-gel pyrolysis is a promising method for synthesizing excellent magnetic biochar adsorbents. [Display omitted] • The sawdust-based biochar was prepared by one-pot sol-gel pyrolysis method. • The sol-gel procedure favored the homogeneous distribution of MnFe 2 O 4 in biochar. • MnFe 2 O 4 @SBC had abundant functional groups along with graded pore structure. • The adsorption prformance of MnFe 2 O 4 @SBC overtook commercial activated carbon. • The MnFe 2 O 4 @SBC had good selectivily and real sample applicability for DCF removal. [ABSTRACT FROM AUTHOR]

[Display omitted] To improve the measurement resolution and accuracy of the grating displacement sensor, this paper proposes an image signal denoising method of grating linear displacement sensors based on NLM. Firstly, the optical system is designed to load the displacement information into the fringe image based on the grating pitch; Then, the principle of NLM image denoising is studied, and the inverse ratio kernel NLM denoising algorithm is designed; Thirdly, the effect of denoising algorithm is compared with the typical kernel function; Finally, the optimized image is used for displacement demodulation. The experimental results show that the SNR of the image is 30.1370db after denoising by this algorithm, and the high-precision displacement stage is set at 20 nm, 40 nm, and, 60 nm. Using the method in this paper, the positioning can be calculated to 22.7 nm, 38.2 nm, and 63.3 nm, and the sub-pixel positioning of the image and the nanopositioning measurement of the displacement are completed. [ABSTRACT FROM AUTHOR]

Using unmanned aerial vehicle (UAV) hyperspectral images to accurately estimate the chlorophyll content of summer maize is of great significance for crop growth monitoring, fertilizer management, and the development of precision agriculture. Hyperspectral imaging data, analytical spectral devices (ASD) data, and SPAD values of summer maize in different key growth periods were obtained under the conditions of a micro-spray strip drip irrigation water supply. The hyperspectral data were preprocessed by spectral transformation methods. Then, several algorithms including Findpeaks (FD), competitive adaptive reweighted sampling (CARS), successive projections algorithm (SPA), and CARS_SPA were used to extract the sensitive characteristic bands related to SPAD values from the hyperspectral image data obtained by UAV. Subsequently, four machine learning regression models including partial least squares regression (PLSR), random forest (RF), extreme gradient boosting (XGBoost), and deep neural network (DNN) were used to establish SPAD value estimation models. The results showed that the correlation coefficient between the ASD and UAV hyperspectral data was greater than 0.96 indicating that UAV hyperspectral image data could be used to estimate maize growth information. The characteristic bands selected by different algorithms were slightly different. The CARS_SPA algorithm could effectively extract sensitive hyperspectral characteristics. This algorithm not only greatly reduced the number of hyperspectral characteristics but also improved the multiple collinearity problem. The low frequency information of SSR in spectral transformation could significantly improve the spectral estimation ability for SPAD values of summer maize. In the accuracy verification of PLSR, RF, XGBoost, and the DNN inversion model based on SSR and CARS_SPA, the determination coefficients (R2) were 0.81, 0.42, 0.65, and 0.82, respectively. The inversion accuracy based on the DNN model was better than the other models. Compared with high-frequency information, low-frequency information (DNN model based on SSR and CARS_SPA) had a strong estimating ability for SPAD values in summer maize canopy. This study provides a reference and technical support for the rapid non-destructive testing of summer maize. [ABSTRACT FROM AUTHOR]

[Display omitted] • Fitting drought intensity and yield loss rate to construct sensitivity curves. • Considering millet planting climatic suitability as a potential exposure index. • A perfect index system suitable for millet drought risk assessment was built. • Distribution and dynamic migration characteristics of millet drought risk were analyzed. Due to the improvement of living standards and the adjustment of dietary structure, the cereal industry shows excellent growth prospects. Clarifying millet drought risk distribution and determining its dynamic evolution characteristics are therefore of great importance for guiding millet production, preventing drought risks, and ensuring food security. In this study, SPRI was used to identify millet drought, and drought intensity-yield loss rate curves were constructed to characterize millet drought sensitivity. The potential exposure of millet was explored by considering millet climatic suitability and farmland proportion. In light of this, a comprehensive assessment of millet drought risk in different growth periods was made using natural disaster risk theory. The results showed that: (1) The sensitivity model for each growth period had passed the F-test of α = 0.05 (R2 were 0.544, 0.408 and 0.347 respectively), reaching a significant level, which proved that the model can be used to assess millet drought sensitivity. (2) More than 70 % of Liaoning Province had a suitable climatic environment for millet production. Combined with the farmland proportion, the area with high potential exposure was distributed in the central region of Liaoning. (3) The millet drought risk in different growth periods showed a characteristic distribution of high in the northwest and low in the southeast. Among them, Chaoyang had the largest high and extremely high drought risk area in the three growth periods, accounting for 92.11 %, 99.34 % and 98.86 % respectively. At the same time, the center-of-gravity model shows that the barycenter of millet drought risk has a trend of spreading from the west of Liaoning to the northeast and southwest. To sum up, the millet drought risk area in Liaoning may increase in the future, measures should be taken to prevent and mitigate millet drought from three aspects: before, during and after the disaster. [ABSTRACT FROM AUTHOR]

Background: Infected pancreatic necrosis (IPN) is a life-threatening complication of acute pancreatitis (AP). Timely diagnosis of IPN could facilitate appropriate treatment, but there is a lack of reliable non-invasive screening tests. In this study, we aimed to evaluate the diagnostic value of plasma metagenomic next-generation sequencing (mNGS) based on circulating microbial cell-free DNA in patients with suspected IPN.Methods: From October 2020 to October 2021, 44 suspected IPN patients who underwent plasma mNGS were reviewed. Confirmatory diagnosis of IPN within two weeks after the index blood sampling was considered the reference standard. The confirmation of IPN relied on the microbiological results of drains obtained from the necrotic collections. The distribution of the pathogens identified by plasma mNGS was analyzed. Positive percent agreement (PPA) and negative percent agreement (NPA) were evaluated based on the conformity between the overall mNGS results and culture results of IPN drains. In addition, the clinical outcomes were compared between mNGS positive and negative patients.Results: Across all the study samples, thirteen species of bacteria and five species of fungi were detected by mNGS. The positivity rate of plasma mNGS was 54.55% (24/44). Of the 24 mNGS positive cases, twenty (83.33%, 95% CI, 68.42-98.24%) were consistent with the culture results of IPN drains. The PPA and NPA of plasma mNGS for IPN were 80.0% (20/25; 95% CI, 64.32-95.68%) and 89.47% (17/19; 95% CI, 75.67-100%), respectively. Compared with the mNGS negative group, patients in the positive group had more new-onset septic shock [12 (50.0%) vs. 4 (20.0%), p = 0.039].Conclusion: IPN relevant pathogens can be identified by plasma mNGS, potentially facilitating appropriate treatment. The clinical application of mNGS in this cohort appears feasible. [ABSTRACT FROM AUTHOR]

www. advancedscience. comVol. 11 • No. 24 • June 26 • 2024 [Extracted from the article]

www. advancedscience. comVol. 11 • No. 24 • June 26 • 2024 [Extracted from the article]

Herein, a broadband ultrasensitive acoustic sensor based on an optical nanofiber coupler (ONC) attached to a diaphragm is designed and experimentally demonstrated. The ONC is sensitive to axial strain and works as the core transducing element to monitor the deformation of the diaphragm driven by acoustic waves. We first theoretically studied the sensing property of the ONC to axial strain and the deformation of the diaphragm. The results reveal that ONC working at the dispersion turning point (DTP) shows improved ultra-sensitivity towards axial strain, and the largest deformation of the circular diaphragm occurs at the center. Guided by the theoretical results, we fabricated an ONC with a DPT at 1550 nm, and we fixed one end of the ONC to the center of the diaphragm and the other end to the edge to construct the acoustic sensor. Finally, the experimental results show that the sensor can achieve accurate measurement in the broadband acoustic wave range of 30~20,000 Hz with good linearity. Specifically, when the input acoustic wave frequency is 120 Hz, the sensitivity reaches 1923 mV/Pa, the signal-to-noise ratio is 42.45 dB, and the minimum detectable sound pressure is 330 μPa/Hz1/2. The sensor has the merits of simple structure, low cost, and high performance, and it provides a new method for acoustic wave detection. [ABSTRACT FROM AUTHOR]

In situ and highly sensitive monitoring of tumor cells provides a fundamental understanding of the valuation of cancer diagnosis. However, existing techniques are largely unable to rapidly capture and precisely quantify the tumor cells. To address this, we propose a novel approach based on a nanotube-functionalized & microfluidic-controlling multiresonance optical fiber sensor. The sensor consists of a tilted fiber Bragg grating (TFBG) inscribed in the fiber core and specially designed halloysite nanotubes (HNTs) coated over the fiber surface. In particular, the HNTs are arranged in an orderly manner along the fiber surface to form slit-like patterned layers for enhanced the interaction with tumor cells, resulting in more effective capture of tumor cells. Such a sensor provides a powerful light scattering sensing ability. Based on the spectral area interrogation method, normal cells and tumor cells can be unambiguously discriminated within a few minutes, providing high sensitivity (limit of detection of 10 cells/mL), and a linear response for a large cell concentration range (10 ∼ 105 cells/mL). Meanwhile, by integrating the fiber sensor with a well-designed microfluidic chip, rapid and precise measurement of different tumor cell samples with low consumption (sub-microliter volumes) can be achieved, which provides a potential tool for cancer diagnosis and treatment. • A novel fiber sensor for tumor cells at very low concentrations is proposed. • A new demodulation method based on the light scattering effect is proposed. • The sensor could rapidly capture of tumor cells through HNTs. • The sensor is promising for the in situ initial screening of tumor cells. [ABSTRACT FROM AUTHOR]

• Realizing excellent fusion of optical fiber and lithium-ion battery. • Implementation of internal temperature monitor by implanting FBG. • FBG sensor displays better signal-to-noise ratio than thermocouple. • The internal temperature is 3.83 °C higher than the external temperature at 2C. • Revealing relationship between charge/discharge rates and temperature gradient. Current cell performance monitoring, which relies on measurements of sporadic surface temperature through the battery management system (BMS), does not provide a reliable information on the true internal battery state. Here we proposed and demonstrated in-operation temperature monitoring of lithium-ion batteries using an implanted femtosecond-laser-inscribed fiber Bragg grating (FBG) sensor. For comparison, both FBG and thermocouple are simultaneously implanted in an 18650 cell. Over repeat cycles with different conditions (0.5C, 1C and 2C), we experimentally demonstrated that implanted FBG and thermocouple sensors show very similar temperature response curves but the FBG sensor provide a much better signal-to-noise ratio. The monitored internal temperature by FBG is 3.71 °C higher than the external temperature during 2C cycling, demonstrating the necessity to record internal temperature especially at long cycles and higher rates within BMS. This operando FBG sensor is a powerful tool in current battery monitoring and its state-of-health evolutions. [ABSTRACT FROM AUTHOR]

Due to global warming, it is necessary to study the influence of extreme climate and concurrent events on crop growth. The study area was the Songliao Plain, where drought events frequently occur. First, the daily meteorological data of 14 meteorological stations from 1981 to 2016 were collected to analyze the temporal and spatial changes in the crop water surplus and deficit index, extreme growing degree-days, and heat stress intensity during different growth stages of maize. Second, the cloud model was used to describe the fuzziness of concurrent events (simultaneous drought and heat), and mutual mapping between qualitative and quantitative data was undertaken. The fuzzy certainty degree of the influence of different degrees of concurrent events on maize was calculated. Third, the copula function was used to describe the randomness of concurrent extreme events and calculate the joint probability distribution and return period. An assessment method was proposed for concurrent events from the perspective of system uncertainty. Finally, we analyzed the relationship between concurrent events and maize yield, which showed different degrees of water deficit and warming trends during each growth period. Crops were most affected by extreme weather during the reproductive growth period (RGP). During the vegetative growth period (VGP), the temperature increase was higher than in other periods, especially in the high-latitude region. The frequency of mild concurrent events was higher during the VGP and RGP. During the vegetative and reproductive period, the average occurrence probability of mild, moderate, and severe concurrent events was 21.9%, 1.7%, and 0.35%, respectively, whereas during the RGP, it was 23.1%, 8.2%, and 0.12%, respectively. The present study provides a meaningful reference for a better understanding of the occurrence laws of drought, heat, and concurrent events during crop growth periods and how to optimize the agricultural management of maize. • Cloud model qualitative and quantitative mapping of drought and heat events. • Copula function was used to describe the randomness of concurrent extreme events. • Vegetative growth periods (VGP) and reproductive growth periods (RGP) were modelled. [ABSTRACT FROM AUTHOR]

• Overall, climate warming is beneficial to sugarcane distribution. • There is a risk of drought in the main sugarcane producing areas. • The cropland fragmentation is significant in sugarcane climate suitable area. • The sugar industry has faced challenges seriously in recent years under global warming and human factors. Guangxi is the primary producer of sugarcane in China and provides a highly suitable habitat for sugarcane growth. However, its distribution range has changed significantly in recent years due to climate change as well as human factors. Without extensive knowledge of the changing trends in suitable sugarcane planting areas, efforts to improve its productivity in Guangxi may be insufficient. In this study, the interdecadal change in sugarcane distribution in Guangxi in response to climate change from 1960 to 2019 was estimated using the MaxEnt model and the landscape pattern of land use in the suitable sugarcane area was analyzed. In addition, we discuss the effects of global warming on sugarcane production in the sustainable development of the sugar industry in Guangxi. Our results indicate: (1) from 1960 to 2019, approximately 65% of Guangxi Province could grow sugarcane. Chongzuo City, Nanning City and Parts of Baise City, are highly suitable areas, and unsuitable areas are mainly concentrated in the north. In general, sugarcane climate suitability extended further in low-altitude areas, and then extended to high- altitude areas. However, from the 2000s to the 2010s, climate suitability showed a decreasing trend, decreasing from 16.036 × 106 ha to 15.4985 × 106 ha (2) The order of land use area in the suitable sugarcane climate range was as follows: woodland > cropland > grassland > construction land > water. With the increase in climate suitability, the distribution of cultivated land expanded. From 1980 to 2005, cropland in suitable areas showed a fragmentation trend. By 2010, the cropland patches disappeared after fragmentation. (3) Due to landscape constraints, infertile soil, and labor costs, the sugar industry faces various challenges. The evaluation of climate suitability could provide a theoretical reference for a planting layout of sugarcane, and landscape pattern analysis of suitable sugarcane climate areas is conducive to the integration of small pieces of land into large ones, making mechanization possible. Overall, strict layout and management measures are required in sugarcane planting areas. [ABSTRACT FROM AUTHOR]