Basic Unit Research Articles

Staggered Assembly of a Dimeric Au13 Cluster: Impacts on Coupling of Geometric Isomerism

AbstractThe specific states of aggregation of metal atoms in sub‐nanometer‐sized gold clusters are related to the different quantum confinement volumes of electrons, leading to novel optical and electronic properties. These volumes can be tuned by changing the relative positions of the gold atoms to generate isomers. Studying the isomeric gold core and the electron coupling between the basic units is fundamentally important for nanoelectronic devices and luminescence; however, appropriate cases are lacking. In this study, the structure of the first staggered di‐superatomic Au25‐S was solved using single‐crystal X‐ray diffraction. The optical properties of Au25‐S were studied by comparing with eclipsed Au25‐E. From Au25‐E to Au25‐S, changes in the electronic structures occurred, resulting in significantly different optical absorptions originating from the coupling between the two Au13 modules. Au25‐S shows a longer electron decay lifetime of 307.7 ps before populating the lowest triplet emissive state, compared to 1.29 ps for Au25‐E. The experimental and theoretical results show that variations in the geometric isomerism lead to distinct photophysical processes owing to isomerism‐dependent electronic coupling. This study offers new insights into the connection between the geometric isomerism of nanosized building blocks and the optical properties of their assemblies, opening new possibilities for constructing function‐specific nanomaterials.

Staggered Assembly of a Dimeric Au13 Cluster: Impacts on Coupling of Geometric Isomerism.

The specific states of aggregation of metal atoms in sub-nanometer-sized gold clusters are related to the different quantum confinement volumes of electrons, leading to novel optical and electronic properties. These volumes can be tuned by changing the relative positions of the gold atoms to generate isomers. Studying the isomeric gold core and the electron coupling between the basic units is fundamentally important for nanoelectronic devices and luminescence; however, appropriate cases are lacking. In this study, the structure of the first staggered di-superatomic Au25 -S was solved using single-crystal X-ray diffraction. The optical properties of Au25 -S were studied by comparing with eclipsed Au25 -E. From Au25 -E to Au25 -S, changes in the electronic structures occurred, resulting in significantly different optical absorptions originating from the coupling between the two Au13 modules. Au25 -S shows a longer electron decay lifetime of 307.7 ps before populating the lowest triplet emissive state, compared to 1.29 ps for Au25 -E. The experimental and theoretical results show that variations in the geometric isomerism lead to distinct photophysical processes owing to isomerism-dependent electronic coupling. This study offers new insights into the connection between the geometric isomerism of nanosized building blocks and the optical properties of their assemblies, opening new possibilities for constructing function-specific nanomaterials.

A novel self-supervised contrastive learning based sentence-level attribute induction method for online satisfaction evaluation

Satisfaction evaluation provides valuable support for procurement decisions and product improvement on e-commerce platforms. As an important task of satisfaction evaluation, attribute induction is essential to identify relevant aspects and demands of user-generated evaluations. However, previous methods have often directly predicted typical attributes using individual words, neglecting valuable sentence-level information that could significantly enhance effectiveness. To alleviate this issue, this article introduces the concept of representations of potential attributes (PARs) to explicitly capture sentence-level information regarding product attributes in customer reviews. It further develops a novel self-supervised contrastive learning based sentence-level attribute induction method (SSCL-SAI) to train these PARs. Recognizing that sentences are the basic units of human expression, this approach mitigates information loss. Then, an aspect-category sentiment analysis model is used to transform the unstructured online textual reviews into linguistic 2-tuple for obtaining final satisfaction evaluation result. These 2-tuples provide a representation of sentiment orientations on a continuous numerical scale, enabling precise linguistic operations. Afterwards, an illustrative example conducted on real-world laptop product satisfaction analysis testify the validity of the approach. Finally, the comparative analysis shows the effectiveness of the proposed SSCL-SAI, and experiments on the impact of hyperparameter settings demonstrate that SSCL-SAI can be applied in various scenarios.

Ultrasensitive electrochemical detection of VEGF based on split aptamers-controlled two-dimensional DNA assembly

In this study, an ultrasensitive electrochemical method is developed for the detection of VEGF based on split aptamers-mediated recognition and subsequently generated two-dimensional DNA products. The sandwich structure formed by split aptamers and VEGF is the basic unit for primary hand-in-hand nanowire assembly and downstream hybridization chain reaction (HCR) as the branched assembly. These events adjust the adsorption capability of DNA probes at the MnO2 nanosheets, which can be well reflected by the electrochemical responses. By analyzing the declined current peak, this VEGF biosensor shows a wide linear range and a limit of detection down to 2 pg/mL. High selectivity and practical utility are demonstrated by experimental results. This method also possesses good extensibility for the design of split aptamers and HCR fuel strands, which exhibits wide application prospects.

Highly Sensitive Fiber Crossbar Sensors Enabled by Second-Order Synergistic Effect of Air Capacitance and Equipotential Body.

Fiber crossbars, an emerging electronic device, have become the most promising basic unit for advanced smart textiles. The demand for highly sensitive fiber crossbar sensors (FCSs) in wearable electronics is increased. However, the unique structure of FCSs presents challenges in replicating existing sensitivity enhancement strategies. Aiming at the sensitivity of fiber crossbar sensors, a second-order synergistic strategy is proposed that combines air capacitance and equipotential bodies, resulting in a remarkable sensitivity enhancement of over 20 times for FCSs. This strategy offers a promising avenue for the design and fabrication of FCSs that do not depend on intricate microstructures. Furthermore, the integrative structure of core-sheath fibers ensures a robust interface, leading to a low hysteresis of only 2.33% and exceptional stability. The outstanding capacitive response performance of FCSs allows them to effectively capture weak signals such as pulses and sounds. This capability opens up possibilities for the application of FCSs in personalized health management, as demonstrated by wireless monitoring systems based on pulse signals.

Cs3In(In4Se7)(P2Se6): A Multi‐Chromophore Chalcogenide with Excellent Nonlinear Optical Property Designed by Group Grafting

AbstractNon‐centrosymmetric (NCS) and polar materials capable of exhibiting many important functional properties are indispensable for electro‐optical technologies, yet their rational structural design remains a significant challenge. Here, we report a “group grafting” strategy for designing the first multi‐chromophore selenophosphate, Cs3In(In4Se7)(P2Se6), that crystallizes in a NCS and polar space group of Cm. The structure features a unique basic building unit (BBU) [In(In4Se10)(P2Se6)], formed through “grafting [In4Se10] supertetrahedra on the root of [In(P2Se6)2] groups”. Theoretical calculations confirm that this [In(In4Se10)(P2Se6)] BBU can achieve a “1+1>2” combination of properties from two chromophores, [In4Se10] supertetrahedron and ethane‐like [P2Se6] dimer. That makes Cs3In(In4Se7)(P2Se6) exhibit excellent linear and nonlinear optical (NLO) properties, including a strong second harmonic generation (SHG) response (~6×AgGaS2), a large band gap (2.45 eV), broad infrared (IR) transmission (up to 19.5 μm), a significant birefringence (0.26 @1064 nm) as well as the congruently‐melting property at ~700 °C. Therefore, Cs3In(In4Se7)(P2Se6) will be a promising NLO crystal, especially in the IR region, and this research also demonstrates that “group grafting” will be an effective strategy for constructing novel polar BBUs with multi‐chromophore to design NCS structures and high‐performance IR NLO materials.

Graphitization: Microstructural and microtextural transformations of residual char from international coal combustion ash

Natural graphite is a critical raw material and its substitution in some applications will contribute to reduce its supply risk. Coal ash, which is still produced in high amounts, contains a carbonaceous solid residue (char) that may be a substitute of natural graphite. For this purpose, char may be graphitized and used in electrocatalysis reactions, however char properties depend on coal rank, composition and combustion conditions that affect the graphitization process. Research on industrial coal char graphitization is limited, resulting in restricted comprehension of the contributing factors. In order to provide novel insights, industrial residual chars (derived from Poland, Portugal, Romania and South Africa) subjected to high-temperature treatments (carbonization at 1000 °C followed by treatment at 2600 °C under environmental pressure) were examined regarding their microstructural and microtextural transformations. The samples were studied by focussing on its heterogeneity, namely its specific properties and interactions, including elemental composition, optical character, and structure. Furthermore, the evolution of structural order of selected char morphotypes in samples derived from coal of similar rank was assessed using Raman microspectroscopy.The results highlighted a set of aspects that could have influenced the transformations experienced by the different chars during high temperature treatments (graphitization). It was found that Hydrogen might play a role in the graphitization ability of isotropic chars derived from low rank coal. The prior preferential orientation of the Basic Structural Units (BSU) contributes to achieve a higher graphitization degree, but it can be enhanced or hindered by other factors, e.g., hydrogen content. Raman microspectroscopy showed that char morphotypes from the same group underwent different transformations during graphitization, indicating that morphotypes or sections with unfused optical character may be more prone to graphitization. However, the existence of disordered domains and specific microtextures, such as polyhedral pores identified under TEM, likely hindered further graphitization. Further research on this topic is needed.

HIFINet: Examination-Diagnosis-Treatment Hierarchical Feedback Interaction Network for Medication Recommendation

Medication combination recommendation is critical in clinic, since accurately predicting therapeutic drug can provide essential decision support to physicians. However, current approaches do not consider the multilevel structure of electronic health record (EHR) data or the hierarchical dependencies between multiple visits, leading to suboptimal recommendations. To address these limitations, we propose a novel hierarchical feedback interaction network (HIFINet) to utilize an examination-diagnosis-treatment hierarchical network for modeling the inherent multilevel structure of EHR data. The feedback long short-term memory network called FeLSTM, which is the basic unit of our hierarchical network, performs hierarchical interactions and leverages change information as feedback to propagate forward among different levels. Additionally, HIFINet contains four modules. First, an embedding module is designed to learn the health information representation of patients. Second, a three-layer time-series learning module is employed to capture temporal dependencies within each sequence. Next, a differential feedback interaction module is developed to capture the difference features between visits. Finally, an attention fusion module is used to learn a comprehensive representation of the patient’s health information and to recommend next multiple treatment medications. HIFINet is compared with state-of-the-art approaches on a real-world dataset. The results indicate that HIFINet outperforms other approaches, offering more accurate recommendations.

THE CONCEPT OF TIME, LENGTH AND MASS

Here I have tried to derive basic units of nature namely, time, distance and mass in terms of Energy and force fields surrounding it. I have made a few changes in the standard definition of Energy in order to arrive at the equations of the three quantities in terms of Energy , force and speed of light ‘c’. Energy is the ability to do work , so it is a latent quantity , it also has the ability to manifest itself in the form of electromagnetic radiation and other forms of energy. Force can be stated as the latent ability to cause change in the state of a body, which can manifest itself as the gravitational force of attraction. Considering these two as the basic units and also the speed of light , I have tried to derive the equation of time , distance and mass in relation to energy and force fields and also speed of light C.

The Influence of Time Domain on Flood Season Segmentation by the Fisher Optimal Partition Method

Setting the staged flood limit water level (FLWL) through flood season staging is an important means of fully utilizing reservoir flood resources. The widely-used Fisher optimal partition method requires a certain time domain as the basic unit in determining the optimal staging of a flood season. Currently, 5 and 10 days matching the month and solar terms are usually used as the time unit. This study aimed to analyze the influence of other time-domain units (7 and 15 days) that meet the relevant requirements on the staging results and to provide a scientific basis for the selection of time-domain units in flood season staging. The rationality of the staging scheme was tested using the improved Cunderlik method, and the influence of specific basic units in the Fisher optimal partition method on the staging results was evaluated. The highest relative superiority of 0.9876 was found for 5 d, indicating that this is a suitable time-domain unit. The optimal staging result was determined as 20 June for the first segmentation point and 20 August for the second. A comparison of the staged FLWL with a single fixed FLWL showed that the water level was raised by 1.56 m in the pre-flood season, 0.65 m in the main flood season, and 1.37 m in the post-flood season. Water storage increased by 12.79 million m3 during the flood season, effectively alleviating the mismatch between water supply and storage.

The greenhouse gas emissions from meat sheep production contribute double of household consumption in a Eurasian meadow steppe

With the rapid development of the economy, household activities have emerged as an important source of greenhouse gas (GHG) emissions, making them a crucial focal point for research in the pursuit of sustainable development and carbon emission reduction. Hulunber, as a typical steppe region in eastern Eurasia, is representative of studying the GHG emissions from household ranches, which are the basic production units in this region. In this paper, based on survey data of 2018 and 2019, we quantified and assessed GHG emissions from household ranches by combining life cycle assessment (LCA) and structural equation modeling (SEM) approaches, with LCA to define household ranches system boundary and SEM to determine the key driving factors of emissions. The results showed that GHG emissions of meat sheep live weight was 23.54 kg CO2-eq/kg. The major contributor to household GHG emissions was enteric methane (55.23 %), followed by coal use (20.80 %) and manure management systems (9.16 %), and other contributing factors (14.81 %). The SEM results indicated that the GHG emissions from household ranches were derived primarily by economic level, while the economic level was significantly affected by income. This study also found a significant positive and linear correlation between household GHG emissions and the number of meat sheep (R2 = 0.89, P < 0.001). The GHG emissions from meat sheep production (67.52 %) were double times greater than household livelihood consumption (32.48 %). These findings emphasized the importance of reducing emissions from meat sheep production and adjusting the energy mix of household livelihood, contributing to the establishment of a low-carbon household livelihood operation.

A Multi-Attention Feature Distillation Neural Network for Lightweight Single Image Super-Resolution

In recent years, remarkable performance improvements have been produced by deep convolutional neural networks (CNN) for single image super-resolution (SISR). Nevertheless, a high proportion of CNN-based SISR models are with quite a few network parameters and high computational complexity for deep or wide architectures. How to more fully utilize deep features to make a balance between model complexity and reconstruction performance is one of the main challenges in this field. To address this problem, on the basis of the well-known information multi-distillation model, a multi-attention feature distillation network termed as MAFDN is developed for lightweight and accurate SISR. Specifically, an effective multi-attention feature distillation block (MAFDB) is designed and used as the basic feature extraction unit in MAFDN. With the help of multi-attention layers including pixel attention, spatial attention, and channel attention, MAFDB uses multiple information distillation branches to learn more discriminative and representative features. Furthermore, MAFDB introduces the depthwise over-parameterized convolutional layer (DO-Conv)-based residual block (OPCRB) to enhance its ability without incurring any parameter and computation increase in the inference stage. The results on commonly used datasets demonstrate that our MAFDN outperforms existing representative lightweight SISR models when taking both reconstruction performance and model complexity into consideration. For example, for ×4 SR on Set5, MAFDN (597K/33.79G) obtains 0.21 dB/0.0037 and 0.10 dB/0.0015 PSNR/SSIM gains over the attention-based SR model AFAN (692K/50.90G) and the feature distillation-based SR model DDistill-SR (675K/32.83G), respectively.

Покращення динамічних властивостей засобу рухомості озброєння шляхом встановлення дизельних двигунів при проведенні модернізації

This article examines the possibilities of improving the dynamic properties of a weapon vehicle by installing diesel engines during modernization. It proposes a number of practical measures to achieve this goal, such as replacing a gasoline engine with a diesel engine.The article conducts a comparative analysis of the traction and dynamic characteristics of the basic gasoline power unit and the diesel power unit installed after modernization on the example of APCS 70. The necessity of modernization by replacing gasoline engines with diesel units is substantiated by means of a comparative traction and dynamic calculation and economic indicators of power units. A comparative analysis of fuel consumption is carried out and the power of the power units is compared. The disadvantages of using gasoline power units are analyzed. According to the results of the calculations, the optimal ratio of parameters that determine the dynamic properties of the vehicle of the weapon is achieved.For the calculation of the main indicators of traction and speed properties of the prototype, the numerical values of the design parameters of the APCS 70 product, which are given in the reference literature, are used.The modernization discussed in this article involves further refinement of the APCS 70's power plant compartment, which is located in the aft part of the hull. It contains two ZMZ 4905 power units assembled with clutches and gearboxes mounted on a common frame. The gasoline power units are replaced with clutch assemblies and 4-speed transmissions. Diesel power units are assembled with clutches, equipped with 5-speed gearboxes and are installed with minor modifications to the standard subframe on which the units are mounted. In turn, the replacement of the power units entails further modifications to the cooling system, fuel supply, exhaust system, engine heating system, as well as part of the electrical equipment of the power units. The transfer case and subsequent transmission of the product remain unchanged.The research provides valuable information for military equipment specialists and engineers interested in improving the performance of combat vehicles.

Efficient Room Temperature Ethanol Vapor Sensing by Unique Fractal Features of Tin Oxide

Fractals are complex structures that repeat themselves at several scales. Nature exhibits these in many forms like snowflakes, mountains, coastlines, the human brain/lungs/ nervous system, and many more. It appears that these are nature’s organic way of growth. Thus, there is an underlying science that works to grow or create these self-similar patterns. In this work, tin oxide-based fractals have been grown under laboratory conditions and applied to a gas-sensing field. The facile growth methodology successfully grows fractals on a large scale. The tin oxide fractals have unique basic building units that connect and grow in different directions. These tin oxide fractals have successfully sensed ethanol vapors in the range of 20 ppm to 100 ppm. The best sensing response has also detected ethanol vapors as low as 10 ppm at room temperature with response and recovery times of 18 ± 3 s and 22 ± 5 s, respectively. The best sensing response recorded for such sensors was under 12 s. The characteristic fractal growth is attributed as the defining factor that enhances ethanol sensing at room temperature.

A practical algorithm for the design of multiple-sized porous scaffolds with triply periodic structures

In this study, we present a practical volume-merging method for generating multiple-sized porous structures that exhibit geometries with triply periodic minimal surface (TPMS) lattice structures. The proposed method consists of three stages: (1) designing the physical models with a signed distance field, (2) performing a merging operation for the porous scaffolds, and (3) assembling different units into a composite structure. The significant advantages of the proposed algorithm can be summarized as follows: Our method is independent of the model shape; the designed structures maintain a smooth surface with a constant mean curvature, and the mathematical computational complexity is low. We can join two different-sized triply periodic minimal surface lattices in the radial direction, where the transition region is obtained by smooth interpolation between the two lattice structures with different cell sizes or types. However, constructing large-sized models is only conceptually possible due to computational cost and memory storage constraints. To overcome these limitations, we present a practical method that can efficiently assemble large-scaled models at a low computational cost. The proposed method is based on a Boolean union operation of basic units of TPMS. Thus, it is simple to generate large-scale three-dimensional multiple-sized porous volumes based on our proposed method, which can be applied to many applications in mechanical and electrical engineering. The produced multi-scale compound scaffolds have smooth surfaces without fractures, making them suitable for straightforward application in additive manufacturing. Several numerical tests are conducted to validate the efficiency of the proposed algorithm.

Preparation and mechanical properties of biomimetic mineralization collagen for dopamine-polyacrylamide-induced small intestinal submucosa

Bone-like lamellar hydroxyapatite(HAP) was successfully synthesized by biomimetic mineralization on small intestinal submucosa(SIS) induced by dopamine(DA)-polyacrylamide (PAM).HAP was uniformly grown by the method of “collagen fiber active site-regulated ion nucleation growth” on SIS film by a lab-built ion diffusion experimental system. The hydrophilic angles before and after SIS modification were 85.3 ± 1.3° and 35.7 ± 1.2°, respectively. The morphology of grow HAP crystals was similar to that of nature bone. Then, DA-PAM@SIS/HAP material was prepared to mimic bone components and basic unit microstructure of natural bones. The tensile strength of composites was about 12 MPa, which was 2.4 times higher than that of the unmineralized films. The mineralized film should be expectedto be applied in the field of bone remodeling and bone tissue engineering.

CESA-MCFormer: An Efficient Transformer Network for Hyperspectral Image Classification by Eliminating Redundant Information.

Hyperspectral image (HSI) classification is a highly challenging task, particularly in fields like crop yield prediction and agricultural infrastructure detection. These applications often involve complex image types, such as soil, vegetation, water bodies, and urban structures, encompassing a variety of surface features. In HSI, the strong correlation between adjacent bands leads to redundancy in spectral information, while using image patches as the basic unit of classification causes redundancy in spatial information. To more effectively extract key information from this massive redundancy for classification, we innovatively proposed the CESA-MCFormer model, building upon the transformer architecture with the introduction of the Center Enhanced Spatial Attention (CESA) module and Morphological Convolution (MC). The CESA module combines hard coding and soft coding to provide the model with prior spatial information before the mixing of spatial features, introducing comprehensive spatial information. MC employs a series of learnable pooling operations, not only extracting key details in both spatial and spectral dimensions but also effectively merging this information. By integrating the CESA module and MC, the CESA-MCFormer model employs a "Selection-Extraction" feature processing strategy, enabling it to achieve precise classification with minimal samples, without relying on dimension reduction techniques such as PCA. To thoroughly evaluate our method, we conducted extensive experiments on the IP, UP, and Chikusei datasets, comparing our method with the latest advanced approaches. The experimental results demonstrate that the CESA-MCFormer achieved outstanding performance on all three test datasets, with Kappa coefficients of 96.38%, 98.24%, and 99.53%, respectively.

County-Level Land Use Carbon Budget in the Yangtze River Economic Belt, China: Spatiotemporal Differentiation and Coordination Zoning

The local land use carbon budget (LUCB) balance is an important factor in achieving regional carbon neutrality. As the basic unit of China’s economic development and social governance, the county level is an important part of the realization of the “double carbon” goal. This paper focuses on 1069 county units within the Yangtze River Economic Belt (YREB). It utilizes data on land use, nighttime light, energy consumption, and social and economic factors to construct carbon emission models. The spatiotemporal characteristics of LUCB in these county units are analyzed using standard deviational ellipse (SDE) and spatial autocorrelation methods. Additionally, a zoning study is conducted by examining the economic contribution coefficient (ECC) of carbon emissions, the ecological support coefficient (ESC), and their coupling relationship. The results show that (1) the total land use carbon emissions (LUCE) increased significantly during the research period, and the total carbon sink was relatively stable. (2) The LUCB is spatially high in the east and low in the west, with the center of gravity moving to the southwest as a whole. (3) The LUCB shows positive spatial autocorrelation and has significant spatial agglomeration characteristics, which are mainly high–high and low–low regional agglomeration types. (4) The ECC is high in the east and low in the west, the ESC is high in the west and low in the east, and the coordination and coupling degrees of the two are low. (5) According to the ECC and ESC, the county unit is divided into a low-carbon conservation area, an economic development area, a carbon sink development area, and a comprehensive optimization area. This study is helpful in promoting the sustainable development of carbon neutrality and low carbon in the YREB.

Mapping cumulative compound hydrometeorological and marine-induced risks on the NW Mediterranean coast

Coastal risks in the Mediterranean are a result of the complex interplay between hydrometeorological and marine hazards. The region encompasses areas with varying degrees of vulnerability to these hazards, as well as spatial variations in exposure values, making it essential to adopt a comprehensive and nuanced approach to risk assessment and management. It is worth noting that hydrometeorological hazards, such as flash floods, can often have a greater impact than strictly coastal hazards, highlighting the need to consider the full range of potential risks. Therefore, coastal managers must adopt a multi-hazard approach to make sound risk management decisions. This study addresses this need using an index-based framework that assesses the integrated risk in time and space (hereafter referred to as cumulative compound risk) in coastal zones by aggregating the main hydrometeorological and marine hazards, the vulnerability of the territory to both types of hazards, and values at exposure. The framework is designed for use at large spatial scales (applied to a 1100 km coastline in this study), with the basic spatial unit being relevant for management (here set as the municipality in this study). Its application enables the assessment of spatial variations in integrated risk as well as individual hydrometeorological and marine contributions. The combined use of the indices and cluster analysis helps identify similarities and differences in the risk profile of spatial units, and thus, define homogeneous areas from a risk management perspective. In this study, the framework was applied to the Spanish Mediterranean coastline, an area representative of the climatic, geomorphological, and socioeconomic conditions of the Mediterranean coast.

Macrocyclic Diacetylene / Sulfonate Fluorophore Hierarchical Multifunctional Nanotoroids.

Functional supramolecular materials exhibit important features including structural versatility and versatile applications. Here, this study reports the construction of unique hierarchically organized nanotoroids exhibiting fluorescence, photocatalytic, and sensing properties. The nanotoroids comprise of macrocyclic diacetylenes (MCDA) and 8-anilino-1-naphthalene sulfonate (ANS), a negatively charged aromatic fluorescent dye. This study shows that the hierarchical structure of the nanotoroids consist of MCDA nanofibers formed by stacked diacetylene monomers as the basic units, which are further bent and aligned into toroidal organization by electrostatic and hydrophobic interactions with the ANS molecules. The amine moieties on the nanotoroids surface are employed for deposition of gold nanostructures - Au nanoparticles or Au nanosheets - which constitute effective platforms for photocatalysis and surface enhanced Raman scattering (SERS)-based sensing.