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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]

Latent Dirichlet Allocation (LDA) is a popular tool for analyzing discrete count data such as text and images, which are required to model datasets and a large number of topics, e.g., tens of thousands of topics for industry scale applications. Although distributed CPU systems have been used to address this problem, they are slow and resource inefficient. GPU-based systems have emerged as a promising alternative because of their high computational power and memory bandwidth. However, existing GPU-based LDA systems can only learn thousands of topics, because they use dense data structures, and have linear time complexity to the number of topics. In this article, we propose SaberLDA, a GPU-based LDA system that implements a sparsity-aware algorithm to achieve sublinear time complexity to learn a large number of topics. To address the challenges introduced by sparsity, we propose a novel data layout, a warp-based sampling kernel, an efficient sparse matrix counting method, and a fine-grained load balancing strategy. SaberLDA achieves linear speedup on 4 GPUs and is 6–10 times faster than existing GPU systems in thousands of topics. It can learn 40,000 topics from a dataset of billions of tokens in two hours, which was previously only achievable using clusters of tens of CPU servers. [ABSTRACT FROM AUTHOR]

Highlights • We propose the Vernier effect induced by the birefringence in fiber-optic modal interferometers for sensitivity enhancement. • We experimentally demonstrate an ultrahigh RI sensitivity of 35,823.3 nm/RIU at low RI of 1.333 using a fiber coupler with the Vernier effect. • We apply this sensor for human cardiac troponin T detection, and a LOD of 1 ng/mL is achieved. Abstract We report a simple and effective method to improve the sensitivities of fiber-optic modal interferometers with birefringence induced Vernier effect. Taking optical microfiber coupler as an example, we study the sensitivity enhancement of a microfiber coupler for refractive index (RI) sensing both theoretically and experimentally in the RI range of 1.33–1.35 where bioassays are typically carried out. Numerical results show that by tracing the wavelength shifts of dips in the envelope formed by the Vernier effect, RI sensitivities can be improved by almost one order of magnitude compared to the sensors without the Vernier effect. Then we experimentally achieve an ultra-high sensitivity of 35,823.3 nm/RIU using a microfiber coupler with a width of 3.2 μm. More importantly, we apply this ultra-sensitive sensor to detect human cardiac troponin, and a limit of detection of 1 ng/mL is achieved. This sensor is simple in configuration andcan serve as a bio-photonic platform for clinical diagnostics environmental monitoring and food safety. [ABSTRACT FROM AUTHOR]

Polycrystalline ferrites Ni 0.5- x Cu 0.12 Zn 0.4 Co x Fe 1.98 O 4- δ with different cobalt-substituted contents ( x  = 0, 0.003, 0.006, 0.009, 0.012, 0.015) are synthetized via the solid-state reaction method. The magnetocrystalline anisotropy constant is calculated based on the law of approach to saturation. As the amount of cobalt substitution increases, the absolute value of the magnetocrystalline anisotropy constant first decreases and then rises due to the positive compensation by the Co 2+ ions. The value of the magnetocrystalline anisotropy constant tends to be zero for the samples with cobalt substitution contents in the range of 0.003–0.006. Meanwhile, when the cobalt substitution content is 0.003, the NiCuZn ferrite shows minimum ferromagnetic resonance linewidth (9.87 kA/m) and low dielectric loss tangent (tg δ ε , 1.1 × 10 −4 ) at 9.4 GHz as well as a high magnetization ( M s , 406 kA/m) and high squareness ratio ( B r / B s , 0.83). Furthermore, the linewidth contribution is identified by the anisotropy and porosity linewidth broadening model based on the spin-wave approach, and the results show that porosity linewidth broadening is the predominant effect. [ABSTRACT FROM AUTHOR]

Sensitive detection of cardiac biomarkers is critical for clinical diagnostics of myocardial infarction (MI) while such detection is quite challenging due to the ultra-low concentration of cardiac biomarkers. In this work, a label-free immunosensor based on optical microfiber coupler (OMC) has been developed for the ultrasensitive detection of cardiac troponin I (cTnI), a selective and highly sensitive biomarker of acute myocardial infarction (AMI). CTnI monoclonal antibodies were immobilized on the surface of the fiber through polyelectrolyte layer using layer-by-layer deposition technique. For refractive index sensing characterization, an ultra-high sensitivity of 91777.9 nm/RIU was achieved when the OMC works around the dispersion turning point, which is the highest experimental demonstration in the field of fiber-optic evanescent biosensors. For biosensing, the immunosensor with good specificity showed a linear wavelength shift in the range of 2–10 fg/mL and an ultra-low detection limit of 2 fg/mL. Such immunosensors have huge application potential for the detection of cardiac biomarkers of myocardial infarction due to simple detection scheme, quick response time, ease of handling and miniaturation. [ABSTRACT FROM AUTHOR]

All-in-fiber optofluidics is an analytical tool that provides enhanced sensing performance with simplified analyzing system design. Currently, its advance is limited either by complicated liquid manipulation and light injection configuration or by low sensitivity resulting from inadequate light–matter interaction. In this work, we design and fabricate a side-channel photonic crystal fiber (SC-PCF) and exploit its versatile sensing capabilities in in-line optofluidic configurations. The built-in microfluidic channel of the SC-PCF enables strong light–matter interaction and easy lateral access of liquid samples in these analytical systems. In addition, the sensing performance of the SC-PCF is demonstrated with methylene blue for absorptive molecular detection and with human cardiac troponin T protein by utilizing a Sagnac interferometry configuration for ultra-sensitive and specific biomolecular specimen detection. Owing to the features of great flexibility and compactness, high-sensitivity to the analyte variation, and efficient liquid manipulation/replacement, the demonstrated SC-PCF offers a generic solution to be adapted to various fiber-waveguide sensors to detect a wide range of analytes in real time, especially for applications from environmental monitoring to biological diagnosis. [ABSTRACT FROM AUTHOR]

Scalable fabrication of spherical particles at both the micro- and nanoscales is of significant importance for applications spanning optical devices, electronics, targeted drug delivery, biodevices, sensors, and cosmetics. However, current top-down and bottom-up fabrication methods are unable to provide the full spectrum of uniformly sized, well-ordered, and high-quality spheres due to their inherent restrictions. Here, a generic, scalable, and precisely controllable fabrication method is demonstrated for generating spherical particles in a full range of diameters from microscale to nanoscale. This method begins with a macroscopic composite multimaterial solid-state preform drawn into a fiber that defines precisely the initial conditions for the process. It is then followed by CO2 laser heating to enable the transformation from a continuous fiber core into a series of homogeneous spheres via Plateau-Rayleigh capillary instability inside the fiber. This physical breakup method applies to a wide range of functional materials with different melting temperatures from 400 to 2400 K and 10 orders of difference in fiber core/cladding viscosity ratio. Furthermore, an ordered array of silicon-based whispering-gallery mode resonators with the Q factor as high as 7.1 × 105 is achieved, owing to the process induced ultrasmooth surface and highly crystalline nature. [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]

The recognition of abrin is of great civil and military importance. As an alternative to general detecting techniques, such as enzyme-linked immunosorbent assay (ELISA) and electrochemiluminescence (ECL)-based assay, micro/nano optical fibers (MNFs) for the label-free detection of abrin have been investigated for the first time in this paper. The MNFs fabricated through chemical etching are robust and have excellent mechanical strength for practical applications. This MNF-based biosensors feature fast response, high sensitivity, and low cost. A limit of detection of 10 pg/mL was obtained using a MNF with a waist diameter of circa 1.0 μm, and the typical measurement time was less than 10 min. By taking advantage of the label-free detection, Langmuir kinetics fitting for the dynamic reaction curve suggested a large affinity constant between the antibody and abrin. Regeneration ability of the sensor was also demonstrated by the maintenance of high sensitivity and selectivity after releasing experiments. [ABSTRACT FROM AUTHOR]

Abstract: Sensitive and selective detection for cancer biomarkers is critical in cancer clinical diagnostics. In this work, we report a new optical microfiber (OMF) biosensor using gold nanoparticles (GNPs) as amplification labels for the detection of alpha-fetoprotein (AFP) in serum samples. By combining the unique optical property of OMFs and the strong optical absorption of GNPs, very high sensitivity and selectivity can be achieved. Critical parameters namely fiber diameter and GNP size were optimized for better performance. The limit of detection (LOD) of this sensor for AFP is 0.2ng/mL in PBS and 2ng/mL in bovine serum, which is comparable to conventional assays. The advantages of this biosensor are simple detection scheme, fast response time, and ease of miniaturization, which might make this biosensor a promising platform for clinical cancer diagnosis and prognosis. [Copyright &y& Elsevier]

Highlights: [•] A bent optical fiber taper is proposed for highly sensitive refractive index detection. [•] The peak wavelength is sensitive to external refractive index. [•] The tapered cladding in the downtaper enhances the sensitivity. [•] Higher sensitivity can be obtained from peak at longer wavelength. [•] A high sensitivity of 4000nm/RIU was experimentally obtained. [Copyright &y& Elsevier]

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]

Plant phenology depends largely on temperature, but temperature alone cannot explain the Northern Hemisphere shifts in the start of the growing season (SOS). The spatio–temporal distribution of SOS sensitivity to climate variability has also changed in recent years. We applied the partial least squares regression (PLSR) method to construct a standardized SOS sensitivity evaluation index and analyzed the combined effects of air temperature (Tem), water balance (Wbi), radiation (Srad), and previous year's phenology on SOS. The spatial and temporal distributions of SOS sensitivity to Northern Hemisphere climate change from 1982 to 2014 were analyzed using time windows of 33 and 15 years; the dominant biological and environmental drivers were also assessed. The results showed that the combined sensitivity of SOS to climate change (SCom) is most influenced by preseason temperature sensitivity. However, because of the asymmetric response of SOS to daytime/night temperature (Tmax/Tmin) and non-negligible moderating of Wbi and Srad on SOS, SCom was more effective in expressing the effect of climate change on SOS than any single climatic factor. Vegetation cover (or type) was the dominant factor influencing the spatial pattern of SOS sensitivity, followed by spring temperature (Tmin > Tmax), and the weakest was water balance. Forests had the highest SCom absolute values. A significant decrease in the sensitivity of some vegetation (22.2%) led to a decreasing trend in sensitivity in the Northern Hemisphere. Although temperature remains the main climatic factor driving temporal changes in SCom, the temperature effects were asymmetric between spring and winter (Tems/Temw). More moisture might mitigate the asymmetric response of SCom to spring/winter warming. Vegetation adaptation has a greater influence on the temporal variability of SOS sensitivity relative to each climatic factor (Tems, Temw, Wbi, Srad). More moisture might mitigate the asymmetric response of SCom to spring/winter warming. This study provides a basis for vegetation phenology sensitivity assessment and prediction. [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]

Recently, tunable photonic nanojets (PNJs) utilizing a mask have been investigated to produce narrow PNJs and curved PNJs (photonic hooks, PHs). Herein, a dielectric nano-layer is employed to tune the PNJs from a micro-cylinder. Symmetric and asymmetric illumination caused by the nano-layer are studied separately with finite element method. The results show that, for the symmetric illumination, narrow PNJs and twin PNJs (t-PNJs) can be generated through controlling the width of the layer. For the asymmetric illumination, it has the ability to produce PHs and asymmetric t-PNJs by changing the thickness of the nano-layer. Based on these results, an optical switch for light-route selection depending on the incident light wavelength is presented. This work may have great potential in the fields of optomechanical manipulation, super-resolution imaging and optical nanolithography. [ABSTRACT FROM AUTHOR]

• A quantitative assessment framework for ecosystem drought risk was established. • Nearly 45.4% of ecosystem vegetation in NEC has a moderate or high risk of drought. • Quantitative assessment of vulnerability is the key point to drought risk assessment. • The drought risk patterns driven by climate variability and human activities are different in farmland and natural vegetation. Given the significant increasing trend of droughts in Northeast China (NEC) under climate change, it is of particularly urgency to quantify the drought risk to vegetation in different ecosystems. Based on the theory of risk formation, we developed a quantitative framework for the assessment of ecosystem drought risk that integrates both drought hazard and vulnerability (sensitivity and adaptability). To quantitatively assess the drought risk to different vegetation types in NEC, we used long-term (1982–2015) normalized difference vegetation index (NDVI) data and standardized precipitation evapotranspiration index (SPEI) data. The effects of climate change and non-climatic factors (mainly human activities) on the NDVI dynamics and drought risk were analyzed using the partial least squares regression method to explore key drivers of risk formation. Our findings indicate that almost 45.4% of ecosystem vegetation in NEC is at a moderate or high risk of drought. Our findings indicate that vulnerability is key to NEC drought risk assessment, and adaptability plays an important role in regulating sensitivity. Land cover is the main driving factor for the spatial pattern of drought vulnerability in NEC, and forests have the lowest vulnerability. The impact of climate change on vegetation dynamics in dry years (R2 dry = 0.35) is significantly higher than over the entire study period (R2 all = 0.20). Cropland drought risk is dominated by human activities, whilst woodland and grassland drought risk is controlled by temperature and precipitation variability, respectively. The driving force analysis of vegetation dynamics and drought risk improves our understanding of the mechanisms behind the formation of risk patterns in NEC. Our study provides a basis for land use management and the formulation of drought adaptation options for vegetation types at different growth stages. [ABSTRACT FROM AUTHOR]

Conventional surface enhanced Raman scattering (SERS) substrates are well known for their supreme electromagnetic enhancements and ultrahigh sensitivity in detecting molecules at low concentrations. However, large‐area quasi‐uniform SERS substrates are difficult to achieve by standard top‐down nanofabrication techniques, resulting in fluctuant SERS responses and unwanted fluorescence interferences, which severely limit their performances in practical applications. To tackle these challenges, a large‐scale quasi‐uniform hybrid graphene fragmented‐gold substrate with stable and reproducible SERS readouts as well as large enhancement factors over an ultrawideband spectrum is developed. The hybrid substrate is fabricated via cold‐etching through a controllable break up of a thin gold film followed by a graphene transfer. The stimulated localized surface plasmons interact strongly with the graphene layer, leading to spectrally and spatially modified graphene‐mediated surface enhanced Raman scattering (GSERS) responses. The perfect monolayer graphene of the GSERS substrate prevents adsorbates from the atmosphere and direct contact between bonded molecules and gold, thus reducing the catalytic activity of gold and producing clean, stable, and reproducible molecular Raman signals. The easy‐fabricated hybrid GSERS substrate not only provides a powerful platform to collect robust molecular Raman spectra but also shows great potentials for future mass production of high‐performance nanophotonic devices. [ABSTRACT FROM AUTHOR]

Examining the effects of climate change on spring maize, and its suitability under dynamic cultivation patterns, will aid strategic decision-making for future agricultural adaptation. This paper investigates the climate suitability of spring maize, based on daily data from 50 meteorological stations, and statistics on maize yield and area at the county level in Jilin Province, China, between 1986 and 2015. Based on a significant correlation between the cultivation patterns indicator ≥10 °C accumulated temperature (AAT10) and the average yield (R2 = 0.503), the yield data are used to determine suitable thresholds for meteorological factors under the dynamic cultivation pattern, and a fuzzy fitness approach is used to evaluate the climate suitability. The results showed a good agreement between suitability estimates and scaled observed yields (average d = 0.705). Moreover, good consistency between cultivation patterns, climate suitability and yield show that the late-maturing varieties of maize have gradually moved northward and eastward, and the areas of high suitability and high yield have gradually expanded eastward. In addition, drought and chilling hazard factors limit the suitability of climate resources, especially in the eastern and western regions. [ABSTRACT FROM AUTHOR]

Integration of functional nanomaterials with optical micro/nanofibers (OMNFs) can bring about novel optical properties and provide a versatile platform for various sensing applications. OMNFs as the key element, however, have seldom been investigated. Here, we focus on the optimization of fiber diameter by taking micro/nanofiber-based localized surface plasmon resonance sensors as a model. We systematically study the dependence of fiber diameter on the sensing performance of such sensors. Both theoretical and experimental results show that, by reducing fiber diameter, the refractive index sensitivity can be significantly increased. Then, we demonstrate the biosensing capability of the optimized sensor for streptavidin detection and achieve a detection limit of 1 pg/mL. Furthermore, the proposed theoretical model is applicable to other nanomaterials and OMNF-based sensing schemes for performance optimization. [ABSTRACT FROM AUTHOR]

A scalable and precisely controllable in‐fiber fabrication method, described by Lei Wei and co‐workers in article number 1703245, produces uniformly‐sized, high‐quality, and globally ordered spherical particles in a full spectrum of diameters from micro‐ to nano‐scale. Harnessing a fluid instability phenomenon in fiber drawing achieves spherical particles from a variety of materials with disparate optical, electronic, and thermoelectric properties. [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 this paper, we report the realization of Mie resonances in air using eccentric hollow metallic cylinders. Our numerical results show that electric resonances/magnetic resonances can be selectively generated in a properly-designed eccentric hollow metallic cylinder under TE-/TM-polarization plane wave illuminations, respectively. We find that the critical dimension for Mie resonance generation is the radius of the hollow hole. Finally, two resonant modes supported by a dual-hole cylinder are presented. This study can be highly favorable to various applications, including optical sensing and nonlinear optics. [ABSTRACT FROM AUTHOR]

With the increasing demand of achieving comprehensive perception in every aspect of life, optical fibers have shown great potential in various applications due to their highly-sensitive, highly-integrated, flexible and real-time sensing capabilities. Among various sensing mechanisms, plasmonics based fiber-optic sensors provide remarkable sensitivity benefiting from their outstanding plasmon–matter interaction. Therefore, surface plasmon resonance (SPR) and localized SPR (LSPR)-based hybrid fiber-optic sensors have captured intensive research attention. Conventionally, SPR- or LSPR-based hybrid fiber-optic sensors rely on the resonant electron oscillations of thin metallic films or metallic nanoparticles functionalized on fiber surfaces. Coupled with the new advances in functional nanomaterials as well as fiber structure design and fabrication in recent years, new solutions continue to emerge to further improve the fiber-optic plasmonic sensors' performances in terms of sensitivity, specificity and biocompatibility. For instance, 2D materials like graphene can enhance the surface plasmon intensity at the metallic film surface due to the plasmon–matter interaction. Two-dimensional (2D) morphology of transition metal oxides can be doped with abundant free electrons to facilitate intrinsic plasmonics in visible or near-infrared frequencies, realizing exceptional field confinement and high sensitivity detection of analyte molecules. Gold nanoparticles capped with macrocyclic supramolecules show excellent selectivity to target biomolecules and ultralow limits of detection. Moreover, specially designed microstructured optical fibers are able to achieve high birefringence that can suppress the output inaccuracy induced by polarization crosstalk and meanwhile deliver promising sensitivity. This review aims to reveal and explore the frontiers of such hybrid plasmonic fiber-optic platforms in various sensing applications. [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]

Highlights • An eco-friendly one-step synthesis of β-CD-capped AuNPs is demonstrated. β-CD acts as both reducing and stabilizing agent. • The systematic characterization and study on the formation mechanism, size control and quality of the β-CD-capped AuNPs. • Integration of β-CD-capped AuNPs and microfiber to realize a biosensor with high-performance LSPR behavior, flexibility and small footprint. • Ultralow LOD of cholesterol of 5 aM is achieved, providing extremely low consumption of clinical samples. • Selective detection of cholesterol molecules in human serum is demonstrated, taking a step towards the practical applications. Abstract Plasmonics in conjunction with supramolecular chemistry brings new opportunities for biosensing. Modified with macrocyclic supramolecules, noble metal nanoparticles possess improved biocompatibility and highly efficient biomolecule immobilization and recognition via host-guest interaction. In this work, we synthesize high-quality and monodisperse β-cyclodextrin-capped gold nanoparticles (β-CD-capped AuNPs) in one-step facile and eco-friendly process, where β-CD functions as both reducing and capping agent. Integrated with a microfiber, the β-CD-capped AuNPs deliver promising localized surface plasmon resonance properties and ultralow detection limit of cholesterol molecules of 5 aM. The selective recognition of our proposed biosensor to cholesterol is further verified by interference study and analysis of real human serum samples. This study shows the bright prospects of supramolecular chemistry assisted plasmonics in achieving highly integrated and highly sensitive biosensing with extremely low consumption of clinical samples and small footprint. [ABSTRACT FROM AUTHOR]

Abstract: Advances in functional fabrics enable the realization of wearable devices in the form factor of fibers that can be seamlessly adapted in our daily lives. For mechanical‐related sensing and power generation, piezoelectric materials are particularly favorable because they can convert mechanical shape changes into electric outputs. Electrospinning is a widely applied technique to produce extended length of fiber‐shaped piezoelectric devices. However, this versatile process normally results in randomly distributed fibers with poor electrical properties and limited response to mechanical stimuli. Here, a stretching‐induced alignment method is demonstrated to achieve highly oriented electrospun poly[(vinylidenefluoride‐co‐trifluoroethylene] P(VDF‐TrFE) fibers on a large scale. These globally aligned electrospun P(VDF‐TrFE) fibers exhibit an enhanced piezoelectric property and high mechanical endurance. Using this simple stretching method, a high average output voltage of 80% aligned electrospun P(VDF‐TrFE) fibers is 84.96 mV, about 266% of their original randomly distributed counterpart. Furthermore, when woven into an outfit, the aligned electrospun P(VDF‐TrFE) fiber bundle can work both individually and combined to monitor body gestures including angles of elbow bending and directions of a swinging arm, which may lead to the further development of motion‐tracking technology. [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]

A side-channel photonic crystal fiber (SC-PCF) is proposed and fabricated to serve as a high sensitivity surface enhanced Raman scattering (SERS) sensing platform. The SC-PCF has a solid core with triangular lattice cladding structure, and one third of the cladding is removed intentionally to enable fast liquid infiltration and enlarge effective interaction area between liquid samples and the fiber core guided lightwave. The geometry of the SC-PCF is designed to obtain high evanescent field power in cladding side-channel, high free space coupling efficiency and low transmission loss at the excitation wavelength of 632.8 nm. Rhodamine 6G (R6G) solutions mixed with gold nanoparticles (AuNPs) are used to test the SERS performance of the proposed platform. A low detection limit of 50 fM R6G solution is achieved. Moreover, an accumulative effect of SERS signal along the SERS-active fiber length is demonstrated experimentally, and a numerical–analytical model for backward scattering scheme is developed to investigate the dependence of Raman intensity on fiber length. [ABSTRACT FROM AUTHOR]