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Rocks often have a rate effect on mechanical behaviors and exhibit a negative Poisson's ratio (NPR) effect after being thermally damaged. However, to date, their combined role in mechanical behaviors has not been clarified. This study micromechanically explores the rate and NPR effects on the compressive behaviors of thermal-damaged rocks using the compression-hardening grain-based model (CHGBM) implemented by the Universal Discrete Element Code (UDEC). The original, moderately, and highly thermal-damaged Suizhou granite samples were subjected to unconfined compression tests for calibrating UDEC-CHGBM. With developing thermal damage from the original state, the rock sample decreases in the peak stress and modulus, exhibiting a transition of pre-peak stress-stain relation from the approximately linear to nonlinear, and a transition of Poisson's ratio from the positive (lateral extension) to negative (lateral contraction). Our UDEC-CHGBM reproduced these experimental phenomena with reasonable accuracy. With increasing strain rates, the peak stress and modulus increase in a power law manner. The dynamic increase factors of the peak stress and modulus also increase with enhancing thermal-damaged degrees. Due to the thermal damage, the grain contact increased in the maximum allowable closure, thus enhancing compression-hardening capacity and nonlinear characteristics, resulting in a promotion of the rate effect. Lateral contraction deformation can reduce the proportion and magnitude of the tensile stress within the sample, and inhibit intergranular microcracking. The NPR effect depends on both the degree of thermal damage and strain rate. We shed light on the synergistic effects of the rate and NPR on macro- to micromechanical behaviors of thermal-damaged rocks. [ABSTRACT FROM AUTHOR]

CRISPR diagnostics are effective but suffer from low signal transduction efficiency, limited sensitivity, and poor stability due to their reliance on the trans-cleavage of single-stranded nucleic acid fluorescent reporters. Here, we present CrisprAIE, which integrates CRISPR/Cas reactions with "one to more" aggregation-induced emission luminogen (AIEgen) lighting-up fluorescence generated by the trans-cleavage of Cas proteins to AIEgen-incorporated double-stranded DNA labeled with single-stranded nucleic acid linkers and Black Hole Quencher groups at both ends (Q-dsDNA/AIEgens-Q). CrisprAIE demonstrates superior performance in the clinical nucleic acid detection of norovirus and SARS-CoV-2 regardless of amplification. Moreover, the diagnostic potential of CrisprAIE is further enhanced by integrating it with spherical nucleic acid-modified AIEgens (SNA/AIEgens) and a portable cellphone-based readout device. The improved CrisprAIE system, utilizing Q-dsDNA/AIEgen-Q and SNA/AIEgen reporters, exhibits approximately 80- and 270-fold improvements in sensitivity, respectively, compared to conventional CRISPR-based diagnostics. We believe CrisprAIE can be readily extended as a universal signal generation strategy to significantly enhance the detection efficiency of almost all existing CRISPR-based diagnostics. Current CRISPR diagnostic approaches can be hampered by several limitations, including low signal transduction efficiency and limited sensitivity. Here, the authors present CrisprAIE, an approach based on CRISPR/Cas-mediated "one to more" lighting-up nucleic acid detection using aggregation-induced emission luminogens. [ABSTRACT FROM AUTHOR]

A rock can undergo hardening deformation during compression and have a memory of the hardening action, which can be displayed when unloaded. This compression-hardening memory effect (CHME) is related to the micromechanical response of the heterogeneous rock microstructure. However, to date, the related mechanism has not been fully characterized. Here, we proposed a grain-based model (GBM) implemented by the Universal Distinct Element Code (UDEC) (version 6.0) to reproduce the cyclic compression test of Jinchuan granite and then investigate the CHME mechanism and its influence on the loading/unloading response of the rock. The results showed that the UDEC-GBM by the compression-hardening memory model (CHMM) reproduces the experimental hysteresis and hardening stress‒strain response, while the traditional linear elastic model (LEM) does not. The grain contact causes nonlinear deformation during compression, enhancing its compressive stiffness. When unloaded, the pre-enhanced compressive stiffness can be remembered, leading to hysteresis and plastic deformation. As a result, the synthetic sample can reserve some of the strain energy and create tensile stress zones, inducing intergranular microcracks and intragranular failure zones. As the peak compressive stress applied in the predisturbed stage increases, the CHME strength increases, influencing the deformation and failure of the synthetic rock sample. Overall, the synthetic rock sample's peak compressive strength decreases as the peak compressive stress applied in the predisturbed stage increases. We shed light on the micromechanical mechanism of CHME, which results from the irreversible increase in the compressive stiffness of grain contacts during compression. Highlights: The rock microstructure exhibits the compression-hardening memory effect (CHME), which can be characterized by the grain-based model. CHME stems from the irreversible enhancement of grain contact stiffness under compression. CHME can lead to the concentration of local tensile stress and rock failure upon unloading, thereby influencing subsequent mechanical responses. [ABSTRACT FROM AUTHOR]

Existing Out-of-Distribution (OoD) detection methods address to detect OoD samples from In-Distribution (InD) data mainly by exploring differences in features, logits and gradients in Deep Neural Networks (DNNs). We in this work propose a new perspective upon loss landscape and mode ensemble to investigate OoD detection. In the optimization of DNNs, there exist many local optima in the parameter space, or namely modes. Interestingly, we observe that these independent modes, which all reach low-loss regions with InD data (training and test data), yet yield significantly different loss landscapes with OoD data. Such an observation provides a novel view to investigate the OoD detection from the loss landscape, and further suggests significantly fluctuating OoD detection performance across these modes. For instance, FPR values of the RankFeat (Song et al. in Advances in Neural Information Processing Systems 35:17885–17898, 2022) method can range from 46.58% to 84.70% among 5 modes, showing uncertain detection performance evaluations across independent modes. Motivated by such diversities on OoD loss landscape across modes, we revisit the deep ensemble method for OoD detection through mode ensemble, leading to improved performance and benefiting the OoD detector with reduced variances. Extensive experiments covering varied OoD detectors and network structures illustrate high variances across modes and validate the superiority of mode ensemble in boosting OoD detection. We hope this work could attract attention in the view of independent modes in the loss landscape of OoD data and more reliable evaluations on OoD detectors. [ABSTRACT FROM AUTHOR]

Image smoothing is a long-studied research area with tremendous approaches proposed. However, how to perform high-quality image smoothing with less computational cost still remains a challenging problem. In this paper, we try to solve this problem with a newly proposed global optimization based method named quasi weighted least squares. In our method, the 2D image is first re-ordered into a 1D vector via a newly proposed 2D-to-1D transformation. We then properly remove some original 2D neighborhood connections. The remaining neighboring pixels can simply form 1D neighborhood connections in the transformed 1D vector while they still contain the 2D neighborhood information in the original 2D image space. These together result in a quite compact linear system that can be easily and efficiently solved, which makes our method a fast global image smoothing approach. Our method is on par with the fastest approaches in terms of processing speed, however, it is able to yield comparable performance with the state-of-the-art ones in terms of smoothing quality. Our method can also work as a solver to approximate the weighted least squares problem in complex systems, and it can achieve similar results but runs much faster. The efficiency and effectiveness of our method are validated through comprehensive experiments in several tasks. Our code is publicly available at: https://github.com/wliusjtu/Q-WLS. [ABSTRACT FROM AUTHOR]

Modelling the response of the filled fracture to the stress wave is of great significance for the prediction and prevention of rock mass instability under dynamic loads. An actual stress wave has varied frequencies, amplitudes, and multiple cycles, which makes the filled fracture suffer from cyclic loading/unloading actions. As a result, its mechanic properties such as the stiffness are progressively altered, which can prominently influence stress wave propagation in a feedback manner. However, existing analytical methods face challenges in modelling this dynamic process. Here, we conducted cyclic compression tests on simulated filled fractures. The filled fracture first produced compression-hardening deformation with stiffness increasing. When unloaded, its stiffness was abruptly enhanced compared with the loading case. This enhanced stiffness could be memorized when reloaded till the compressive stress exceeded the historical maximum, after which the filled fracture produced compression-hardening deformation again. Constitutive equations were proposed to characterize the above compressive stress-closure relation and were accurately validated by experimental results. On this basis, we established an analytical model for the propagation of the longitude stress wave through a filled fracture considering cyclic loading/unloading behaviours. It could well reproduce the experimental result on propagation of the stress wave with two main merged pulses through an artificially filled fracture. Parametric studies were conducted to systematically examine the influences of the cyclic loading/loading process, amplitude, and frequency. It was found that cyclic loading/unloading actions to the filled fracture could be memorized and accumulated to a maximum extend, which prominently affected subsequent stress wave propagation. Highlights: A filled fracture produced compression-hardening deformation and its stiffness could be abruptly increased when unloaded. Enhanced stiffness could be memorized when reloaded till the historical maximum compressive stress was exceeded. Cyclic loading/unloading behaviors of the filled fracture significantly influenced the stress wave propagation. [ABSTRACT FROM AUTHOR]

A novel construction strategy is introduced for an ultrasensitive dynamic light scattering (DLS) immunosensor targeting alpha fetoprotein (AFP). This approach relies on a self-assembled heptamer fusion protein (A1-C4bpα), incorporating the dual functions of multivalent recognition and crosslinking aggregation amplification due to the presence of seven AFP-specific A1 nanobodies on the A1-C4bpα heptamer. Leveraging antibody-functionalized magnetic nanoparticles for target AFP capture and DLS signal output, the proposed heptamer-assisted DLS immunosensor offers high sensitivity, strong specificity, and ease of operation. Under the optimized conditions, the designed DLS immunosensor demonstrates excellent linear detection of AFP in the concentration range 0.06 ng mL−1 to 512 ng mL−1, with a detection limit of 15 pg mL−1. The selectivity, accuracy, precision, practicability, and reliability of this newly developed method were further validated through an assay of AFP levels in spiked and actual human serum samples. This work introduces a novel approach for constructing ultrasensitive DLS immunosensors, easily extendable to the sensitive determination of other targets via simply replacing the nanobody sequence, holding great promise in various applications, particularly in disease diagnosis. [ABSTRACT FROM AUTHOR]

Rock materials exhibit different elastic moduli under tension and compression, making them typical bi-modulus materials. Few testing methods can measure both tensile and compressive moduli (Et and Ec) of such materials simultaneously, and with their reliability not systematically validated. Taking blue and red sand rocks as the example, this study performed a series of uniaxial compression, direct tension, Brazilian disc, and three-point bending tests, in which strain gauges and DIC technology were used to observe the deformation. Through comprehensively comparative study, the following findings are obtained: (1) Direct tension and compression tests remain the most reliable methods for measuring the Et and Ec of rock materials. (2) Only the sub-method I based on the Brazilian disc test proposed by Ye et al in (Int J Rock Mech Min Sci 46(3):568–576, 2009a) exhibits good reliability. (3) Three-point bending test is not recommended due to the adverse effect caused by the stress concentration in the region beneath the loading head. (4) Strain gauges theoretically offer a high measurement accuracy, but their results are significantly influenced by artificial factors; while DIC technology demonstrates a higher reliability when strain exceeds a threshold (e.g., > 500). [ABSTRACT FROM AUTHOR]

Dendritic mechanisms driving input-output transformation in starburst amacrine cells (SACs) are not fully understood. Here, we combine two-photon subcellular voltage and calcium imaging and electrophysiological recording to determine the computational architecture of mouse SAC dendrites. We found that the perisomatic region integrates motion signals over the entire dendritic field, providing a low-pass-filtered global depolarization to dendrites. Dendrites integrate local synaptic inputs with this global signal in a direction-selective manner. Coincidental local synaptic inputs and the global motion signal in the outward motion direction generate local suprathreshold calcium transients. Moreover, metabotropic glutamate receptor 2 (mGluR2) signaling in SACs modulates the initiation of calcium transients in dendrites but not at the soma. In contrast, voltage-gated potassium channel 3 (Kv3) dampens fast voltage transients at the soma. Together, complementary mGluR2 and Kv3 signaling in different subcellular regions leads to dendritic compartmentalization and direction selectivity, highlighting the importance of these mechanisms in dendritic computation.How starburst amacrine cell (SAC) dendrites transform concentrically distributed synaptic inputs into branch-specific directional outputs is not fully understood. Here the authors report that dendritic mGluR2 signaling and somatic Kv3-mediated shunting coordinately implement SAC dendritic direction selectivity. [ABSTRACT FROM AUTHOR]

Context: Quantifying the interactions between land disturbances and energy and water balances, particularly evapotranspiration (ET), is helpful for understanding the land-atmospheric interactions and assessing the effects of urbanization on local climate and hydrological processes at a landscape scale. Objectives: To investigate the mechanisms of ecohydrological response to urbanization from the perspectives of ET or energy balances in a distributed fashion at the watershed scale. To identify spatial 'hot spots', in which ET, and thus watershed hydrology, are most pronounced in response to land use change so that limited watershed landscape management resources can be applied efficiently. Methods: This process-based research quantified spatial patterns of ET and other energy fluxes in a rapidly urbanizing rice paddy-dominated watershed, Qinhuai River Basin (QRB), using a spatially explicit land surface energy balance model (SEBAL). Results: The QRB experienced a rapid land use change in urban–rural interface (URI) area, resulting in a significant reduction in actual ET (− 9.4 mm yr−1) but a significant increase in sensible heat (3.71 W m−2 yr−1) and soil heat fluxes (0.85 W m−2 yr−1) during the growing season from 2001 to 2019. The change in energy partitioning at the watershed scale was dominated by URI area identified as the 'hot spots' of ecohydrological change within a heterogeneous basin. Conclusions: Knowledge gained from this study improves parameterizing distributed watershed ecohydrological models (e.g., ET processes) to guide urban planning. Effective watershed landscape management and planning that aims at mitigating the negative impacts of urbanization should focus on URI by preserving vegetation and local wetlands (e.g., rice paddies). [ABSTRACT FROM AUTHOR]

Rapid urban expansion and climate change often bring about loess cave disasters on the Chinese Loess Plateau. It is believed that human activity and rainfall can synergistically alter the hydrogeological conditions and further accelerate the formation of loess caves. However, thus far, few cases or lines of evidence have been reported to support this conclusion. The study provided an example of the formation of loess caves in Weinan city, Loess Plateau, Northwest China, which was related to rainfall and erosion due to pipe breakage and leakage. The precipitation data were collected to examine the effect of rainfall erosion. Moreover, through a field investigation and multi-channel analysis of surface waves (MASW) survey, ten loess caves that were adjacent to aging underground pipes were systematically investigated. The physical and mechanical properties that were affected and unaffected by the loess caves were compared to explore the influence of the pipe breakage and leakage, i.e., the water content, void ratio, and self-weight collapsibility coefficient. The results showed that the spatial variation in these properties could reflect the alteration of the loess caves under the combined action of rainfall and pipe-breakage and leakage erosion. We shed light on this synergistic effect on loess cave formation and proposed a four-stage formation model: formation of the upper negative relief, initiation of the inner cave, upper to lower coalescence, and volume enlarging. New insights were provided on the development process of the loess caves and the synergistic role between human activities and a natural force. The findings can help us to more comprehensively understand the formation mechanisms and development trends of the loess caves to predict and prevent loess cave disasters on the Chinese Loess Plateau. [ABSTRACT FROM AUTHOR]

'Urban Dry (Wet) Islands' (UDI/UWI) represents microclimate change that impacts ecosystems and human well-being. However, causes of the UDI (UWI) phenomena are not fully understood due to the lack of empirical data. Here, we quantify UDI (UWI) using global observations of atmospheric humidity, evapotranspiration (ET), and land surface characteristics across 25 large urban agglomerations. We show that UDI (17) and UWI (8) are closely tied to local ET, global warming, and 'Urban Heat Islands' through intertwined linkages with water and energy balances. UDI is most pronounced in humid vegetated regions where mean urban-rural annual ET differences are as high as 215 mm, whereas UWI is found in arid regions or in climates with dry summers. We conclude that ET can be used as a single variable to explain emerging urban environmental changes. Our study supports a concerted strategy of restoring nature's ET power as effective 'Nature-based Solutions' to mitigate the negative environmental effects of urbanization. [ABSTRACT FROM AUTHOR]

The neural tangent kernel (NTK) has recently attracted intense study, as it describes the evolution of an over-parameterized neural network (NN) trained by gradient descent. However, it is now well-known that gradient descent is not always a good optimizer for NNs, which can partially explain the unsatisfactory practical performance of the NTK regression estimator. In this paper, we introduce the weighted neural tangent kernel (WNTK), a generalized and improved tool, which can capture an over-parameterized NN's training dynamics under adjusted gradient descent direction. Theoretically, in the infinite-width limit, we prove: (1) the stability of the WNTK at initialization and during training, and (2) the equivalence between the WNTK regression estimator and the corresponding NN estimator with different learning rates on different parameters. With the proposed weight update algorithm, weight terms, or equivalently NN descent directions, can be trained through multiple-kernel optimization. Both empirical and analytical WNTKs outperform the corresponding NTKs in numerical experiments, coinciding with the fact that adjusted gradient descent could outperform original gradient descent in NNs' training. [ABSTRACT FROM AUTHOR]

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To study the effects of different soil water conditions on pollen fertility and cottonseed yield, cotton plants were grown under different soil water conditions (normal water regime, waterlogging, mild drought, and medium drought) induced by different groundwater depths. Results showed that compared to the normal water regime, cottonseed yield decreased under waterlogging, mild drought, or medium drought. The mild drought had little effect on seed number per boll (SNB) and seed index, but waterlogging and medium drought had significantly negative effects on them. Weak pollen fertility might be the main reason for the decrease of SNB under waterlogging and medium drought, and the decreased pollen fertility was caused by the inhibited synthesis of starch and adenosine triphosphate in anthers. Waterlogging downregulated the activity of soluble starch synthases (SSSase) and the expression level of GhSSSase gene, but medium drought down-regulated SSSase and adenosine diphosphate-glucose pyrophosphorylase (AGPase) activities and the expression of GhAGPase and GhSSSase genes to impede starch synthesis. Moreover, waterlogging increased anther sucrose content by inhibiting acid invertase activity while medium drought increased the accumulation of sucrose content by decreasing sucrose synthetase activity. Both waterlogging and medium drought down-regulated the expression level of GhHXK gene, resulting in higher glucose content in anthers. Furthermore, increased O2− and H2O2 contents also adversely affected the pollen fertility, and this increase was attributed to lesser activities of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT), and down-regulated gene expression of Cu/Zn SOD, Mn SOD, POD, and CAT. Compared to the medium drought, proline content effectively increased under waterlogging, and a large decrease in SOD activity and Mn SOD gene expression was observed under waterlogging. Our findings suggest that both medium drought and waterlogging affected the carbohydrate and antioxidant metabolism to vitiate pollen viability, ultimately affecting cottonseed development, however, their effects on starch biosynthesis, sucrose decomposition, and antioxidant metabolism were not entirely uniform. These results will improve our knowledge and give us a direction on the mechanism of the tolerance to drought and waterlogging for cotton. [ABSTRACT FROM AUTHOR]

A self-powered X-ray detector based on CH3NH3PbI3 thick film with both electron and hole transport layers has been prepared by a facile and low-cost solution method. The CH3NH3PbI3 thick film has a compact structure and a thickness of 16.5 μm processed by the doctor-blade method. The structure and thickness of CH3NH3PbI3 thick film are helpful to improve its efficiency of directly converting X-ray photons into electron-hole pairs. The photoelectric characteristics and operation mechanism with ions migration of the detector were systematically investigated. Meanwhile, the influence of the migration ions on the performance of the X-ray detector was studied by controlling the poling time of ions migration. After poling process, the sensitivity of the self-powered detector enhanced from 65 to 127 µC Gyair−1 cm− 2 under an irradiation dose rate of 0.1584 mGyair s− 1. Noticeably, with the blade-coating Carbon electrode on the surface of CH3NH3PbI3, the device without encapsulating showed good stability after being exposed to ambient air for two months. [ABSTRACT FROM AUTHOR]

This paper studied the dynamic response of the homogeneous step-like rock slope under wide frequency and amplitude through a large-scale shaking table test. A homogenous rock slope with a length of 3.50 m, width of 0.68 m and height of 1.20 m was constructed in a rigid steel box. Results indicate that acceleration amplification factor in horizontal direction (AAF-X) along the slope surface is amplified with the increase in the slope height when loading frequency ≤ 45 Hz, while AAF-X decreases first then increases when loading frequency is 60 Hz and 75 Hz. The acceleration amplification factor in vertical direction (AAF-Z) increases first and then decreases with the increase in the slope height. The resonance frequency of slope near the slope crest decreases from 61.37 to 58.12 Hz, while the damping ratio increases from 5.8 to 8.8%, as the loading amplitude increases from 0.1 to 0.5 g. The AAF reminds linear increase with a loading amplitude of up to 0.4 g while decreases when the loading amplitude becomes larger than 0.5 g. It reveals that the loading amplitude has a "double-effect" on the seismic response of the homogeneous rock slope. That is, on the one hand, the larger the loading amplitude, the stronger the acceleration intensity, the greater deterioration of rock slope structure or material and the larger damping ratio of the slope; on the other hand, more energy will be dissipated due to plastic deformation or particle friction of high damping ratio and weaker slope structure. Such test result can be used for understanding the dynamic instability mechanism of the homogeneous slope in the field. [ABSTRACT FROM AUTHOR]

Characterization on the response of the jointed rock mass to the stress wave is of great significance for rock engineering and the prevention of dynamic geological disasters. A joint in the rock mass produces discontinuous deformation under dynamic loads and can be weakened on both stiffness and strength, which further affect stress wave propagation in a feedback manner. However, previous numerical models mainly used the linearly elastic model (LEM) (constant stiffness) and the nonlinear Bandis-Barton model (BBM) (compression-strengthening stiffness) to characterize the dynamic response of the rock mass which neglected dynamic damage and stiffness weakening of the joint. To overcome this problem, we adopted a modified BBM (MBBM) to establish an advanced numerical model of the dynamic response of the rock mass by the Universal Distinct Element Code (UDEC). The MBBM is capable of characterizing joint stiffness weakening attributed to the filled particle crushing, which can be also degraded into both LEM and BBM. Our model was well verified by experimental data on stress wave propagation through an artificial filled joint. Dynamic responses of rock masses containing a single joint, a set of parallel joints, and intersected joints were systematically investigated considering the amplitude and incident angle of the incident wave as well as the joint spacing. Results showed that weakening of the joint stiffness had an important impact on the wave transmission and effect of multiple reflections at joints. Compared with previous models, our model has prominent advantages and accuracy in simulating dynamic damage and weakening response of the rock mass. Highlights: A joint constitutive model considering stiffness weakening attribute to filled particle crushing was implemented in UDEC. Dynamic damage of the filled joint and its effect on stress wave propagation was quantitively characterized. Interaction between the stress wave and the rock mass with varied structures was systematically examined. [ABSTRACT FROM AUTHOR]

Ultrabright green-emissive AIE nanoparticles (AIENPs) were used as signal-amplification probes to enhance the detectability of lateral flow immunoassay (LFIA). The detection performances of the green-emissive AIENP probes in both sandwich and competitive LFIA formats were systematically evaluated. Benefiting from its remarkable fluorescent brightness, the developed AIENP-LFIA showed versatile applicability for the detection of small molecules and macromolecules by using ochratoxin A (OTA) and procalcitonin (PCT) as model analytes, respectively. Under the optimum conditions, the detection limits (LODs) of the fabricated AIENP-LFIA for OTA and PCT were 0.043 ng mL−1 and 0.019 ng mL−1, respectively. These LOD values are significantly lower than those of conventional LFIA methods using gold nanoparticles as signal reporters. In addition, we demonstrated the practical application potential of AIENP-LFIA for the detection of OTA in real maize samples and PCT in real serum samples. These results indicated that the ultrabright green-emissive AIENPs were promising as signal output materials for building high-performance LFIA platform and broadening the application scenarios of LFIA. [ABSTRACT FROM AUTHOR]

Risk aversion, which refers to the reluctant attitude of an economic agent to accept uncertain outcomes compared with a certain one even if the latter has a lower outcome in monetary value, plays a fundamental role in decision theory and risk management. This paper investigates how to measure different agents' risk-averse attitudes towards a risky situation consisting of multiple uncertain components under uncertainty theory. First, a general method to approximately compute the multivariate uncertain risk premium is proposed. Subsequently, the multivariate uncertain risk aversion is formally defined based on the multivariate uncertain risk premium, and the corresponding sufficient condition for utility functions being multivariate risk-averse is given. Its relation to Richard's correlation aversion under the framework of uncertainty theory is also discussed. Finally, the suggested theoretical findings are applied to an accounts receivables (ARs) pricing problem to exhibit their applicability. The results show that our method is more applicable in practice than the univariate approach. Moreover, for the AR financing, the AR owner should choose higher-credit trading partners and financial institutions with less risk aversion to cooperate for acquiring more cash. [ABSTRACT FROM AUTHOR]

The 2021 Madoi M7.4 Earthquake in Qinghai is a major earthquake that occurred in the Bajankara Block of Qinghai-Tibet Plateau in the past 30 years, which spatially filled the seismogenic gap in the eastern section of the northern boundary of the block. Here we determined the values of ML, MS_BB, mB, MWp, MWW, Mdt, and M (GNSS) by abundant regional and global seismic and geodetic observations, which is 6.61, 7.43, 7.18, 7.33, 7.43, 7.38, and 7.4, respectively. To compare the time efficiency and stability of different magnitude scales, we generated a real-time environment, to iteratively determine the magnitudes over elapsed times. Some methods such as mB, MSBB, MWp gave considerable variations of as large as 0.5 units for the determined magnitudes with elapsed time, as more data were included. Others such as MWW and Mdt were very stable with increasing data over time. The systematic calculations of various magnitude scales in this study quantitively evaluated the stability and accuracy of those methods, shading light on the adaptability and applicability of different magnitude scales. [ABSTRACT FROM AUTHOR]

Purpose: With the increasing usage of stereo cameras in computer-assisted surgery techniques, surgeons can benefit from better 3D context of the surgical site in minimally invasive operations. However, since stereo cameras are placed together at the confined endoscope tip, the size of lens and sensors is limited, resulting in low resolution of stereo endoscopic images. How to effectively exploit and utilize stereo information in stereo endoscopic super-resolution (SR) becomes a challenging problem. Methods: In this work, we propose a disparity-constrained stereo super-resolution network (DCSSRnet) to reconstruct images using a stereo image pair. In particular, a disparity constraint mechanism is incorporated into the generation of SR images in the deep neural network framework with effective feature extractors and atrous parallax attention modules. Results: Extensive experiments were conducted to evaluate the performance of proposed DCSSRnet on the da Vinci dataset and Medtronic dataset. The results on endoscopic image datasets demonstrate that the proposed approach produces a more effective improvement over current SR methods on both quantitative measurements. The ablation studies further verify the effectiveness of the components of the proposed framework. Conclusion: The proposed DCSSRnet provides a promising solution on enhancing the spatial resolution of stereo endoscopic image pairs. Specifically, the disparity consistency of the stereo image pair provides informative supervision for image reconstruction. The proposed model can serve as a tool for improving the quality of stereo endoscopic images of endoscopic surgery systems. [ABSTRACT FROM AUTHOR]

Acoustic emission (AE) characterization is an effective technique to indirectly capture the failure process of quasi brittle rock. In previous studies, both experiments and numerical simulations were adopted to investigate the AE characteristics of rocks. However, as the most popular numerical model, the moment tensor model (MTM) cannot be constrained by the experimental result because there is a gap between MTM and experiments in principle, signal processing and energy analysis. In this paper, we developed a particle-velocity-based model (PVBM) that enabled direct monitoring and analysis of the particle velocity in the numerical model and had good robustness. The PVBM imitated the actual experiment and could fill in gaps between the experiment and MTM. AE experiments of marine shale under uniaxial compression were carried out, and the results were simulated by MTM. In general, the variation trend of the experimental result could be presented by MTM. Nevertheless, the magnitudes of AE parameters by MTM presented notable differences of more than several orders of magnitude compared with those by the experiment. We sequentially used PVBM as a proxy to analyse these discrepancies and systematically evaluate the AE characterization of rocks from the experiment to numerical simulation, considering the influence of wave reflection, energy geometrical diffusion, viscous attenuation, particle size and progressive deterioration of rock material. The combination of MTM and PVBM could reasonably and accurately acquire AE characteristics of the actual AE experiment of rocks by making full use of their respective advantages. [ABSTRACT FROM AUTHOR]

In this work, we synthesized a novel hyperbranched Au plasmonic blackbody (AuPB) and applied it as a signal amplification label in immunochromatographic test strip (ICTS) sensor for the sensitive detection of aflatoxin B1 (AFB1) in maize. AuPB were characterized with high color signal intensity, superior colloidal stability, and excellent biocompatibility benefiting from the hyperbranched structure and the dense polydopamine layer on surface, which contributes to improving the sensitivity and robustness of competitive ICTS sensor. Under the optimized conditions, the half inhibition concentration and the detection limit of our AuPB-enhanced ICTS (AuPB-ICTS) sensor were 0.087 and 0.016 ng/mL, which are 3.9- and 5.4-fold lower than those of traditional ICTS sensor based on 35-nm gold nanospheres as signal reporters. The average recoveries for the intra- and inter-assay ranged from 92.5 to 119.5%, with the coefficient of variation of 3.29–10.28%. Moreover, the reliability and practicability of this method were validated by the well-established ultra-performance liquid chromatography method via simultaneously measuring fifteen naturally contaminated maize samples. In summary, the developed AuPB-ICTS sensor can serve as an alternative rapid diagnostic method to allow the sensitive and reliable screening of AFB1 in maize. [ABSTRACT FROM AUTHOR]

Qinghai-Tibet Plateau is one of the most seismically active aeras of China and rock mass structures or geological structure are also complex here. Earthquake-induced geological disasters are occurred frequently in this region. Among them, plane failure is often generated on bedding rock slope especially in destructive area of the Wenchuan earthquake which caused numerous casualties and serious economic loss. To reveal failure mechanism of bedding rock slope, this paper studied the seismic response and investigated progressive failure characteristics of the bedding rock slope through a large-scale shaking table test. A bedding rock slope of 45° contained an unfilled joint set with spacing of 0.1 m that dipped at an angle of 34° out of the surface, was conducted in a rigid model box, with a length of 3.47 m, width of 0.68 m, and height of 1.2 m, respectively. A series of tests results show that acceleration amplification factor in horizontal direction (AAF-X) increases with the increase of the slope elevation and acceleration amplification factor in vertical direction (AAF-Z) amplifies at lower part of the slope. When the shaking intensities are over 0.2 g, the slope crest and its vicinity start to show nonlinear dynamic response. Existence of bedding planes let the isoline morphology of AAF-X redistribute and dominate the seismic amplification at the crest. The progressive failure progress of the model under earthquake can be divided into four stages. This novel experiment offers some important insights to mechanism of bedding plane landslides triggered by earthquakes, evaluation stability of slopes under earthquake, and disaster prevention and mitigation. [ABSTRACT FROM AUTHOR]

In this paper, we study the asymptotic properties of regularized least squares with indefinite kernels in reproducing kernel Kreĭn spaces (RKKS). By introducing a bounded hyper-sphere constraint to such non-convex regularized risk minimization problem, we theoretically demonstrate that this problem has a globally optimal solution with a closed form on the sphere, which makes approximation analysis feasible in RKKS. Regarding to the original regularizer induced by the indefinite inner product, we modify traditional error decomposition techniques, prove convergence results for the introduced hypothesis error based on matrix perturbation theory, and derive learning rates of such regularized regression problem in RKKS. Under some conditions, the derived learning rates in RKKS are the same as that in reproducing kernel Hilbert spaces (RKHS). To the best of our knowledge, this is the first work on approximation analysis of regularized learning algorithms in RKKS. [ABSTRACT FROM AUTHOR]

Myoclonus dystonia syndrome (MDS) is an inherited movement disorder, and most MDS-related mutations have so far been found in the ε-sarcoglycan (SGCE) coding gene. By generating SGCE-knockout (KO) and human 237 C > T mutation knock-in (KI) mice, we showed here that both KO and KI mice exerted typical movement defects similar to those of MDS patients. SGCE promoted filopodia development in vitro and inhibited excitatory synapse formation both in vivo and in vitro. Loss of function of SGCE leading to excessive excitatory synapses that may ultimately contribute to MDS pathology. Indeed, using a zebrafish MDS model, we found that among 1700 screened chemical compounds, Vigabatrin was the most potent in readily reversing MDS symptoms of mouse disease models. Our study strengthens the notion that mutations of SGCE lead to MDS and most likely, SGCE functions to brake synaptogenesis in the CNS. [ABSTRACT FROM AUTHOR]

The fractal geometry method has been employed to quantitatively characterize the roughness of a rock discontinuity, which is one of the key factors affecting its shear strength and the seepage characteristics of a rock mass. However, the current fractal methods involving the three-dimensional discontinuity morphology suffer from one or more problems, such as a complicated calculation procedure, an inaccurate calculation result and an inability to characterize the undulation and anisotropy of a discontinuity. To cope with these problems, the discontinuities in artificial granite samples with irregular and undulating surfaces were taken as examples, and a quantitative study on the discontinuity morphology was conducted based on the method of three-dimensional laser scanning in combination with ArcGIS data processing, geographical research, theoretical calculations and regression analysis. After performing systematic research, we proposed an extensive 3D fractal dimension including three discontinuity morphological parameters, i.e. the fractal dimension of discontinuity morphology, the ratio between the maximal undulating amplitude and the discontinuity length, and the average value of all the apparent dip angles of the discontinuity surfaces dipping opposite the shear direction. The extensive 3D fractal dimension can comprehensively characterize the roughness, undulation and anisotropy of the discontinuity morphology. A set of theoretical calculation methods were then developed to determine the three discontinuity morphological parameters of the extensive 3D fractal dimension based on ArcGIS. We finally established a mathematical expression of the extensive 3D fractal dimension. Compared with the current fractal methods, the extensive 3D fractal dimension can effectively compensate for the inability to characterize the undulation and anisotropy of the discontinuity morphology. Its calculation methods have the advantages of simplification, low-time consumption and high precision. [ABSTRACT FROM AUTHOR]

Gold nanoparticle–decorated metal organic frameworks (MOF@AuNPs) with significantly enhanced color signal intensity were synthesized through in situ growth of AuNPs on the MOF skeleton. The resultant MOF@AuNP nanocomposites were characterized with 16.7-fold higher absorbance than conventional 40 nm AuNPs (AuNP40). Thus, for the first time, we applied it as a signal amplification label to improve the immunochromatographic assay (ICA) of human chorionic gonadotropin (HCG). The detection limit of our enhanced ICA was 1.69 mIU/mL, which is ca. 10.6-fold improvement in sensitivity compared to traditional AuNP40-ICA. The recoveries of this MOF@AuNPs-ICA ranged from 86.03 to 119.22%, with coefficients of variation of 3.05 to 13.74%. The reliability and practicability were further validated by the clinically used chemiluminescence immunoassay method. Given their excellent signal amplification ability, the proposed MOF@AuNPs could serve as an ideal ICA label for rapid and sensitive detection of disease biomarkers. [ABSTRACT FROM AUTHOR]

Laboratory tests showed that the average direct tension strength (DTS0) of the Lac du Bonnet granite was 6.9 MPa, and significantly less than its average Brazilian tension strength (BTS0), i.e., 8.8 MPa. In this paper, a grain-based model (GBM) with a 2D universal discrete element code (UDEC) was used to explore factors that could control the difference in the direct tension strength (DTS) and Brazilian tension strength (BTS) of the Lac du Bonnet granite from the micromechanical point of view. Micro parameters of the grain contacts were investigated, i.e., the tensile strength (T), cohesion (c), friction angle (φ), and the ratio of the shear to normal stiffness (λ). Results show that both BTS and DTS highly depended on log(λ). With an increase in log(λ), the BTS first increased nonlinearly and decreased instead after achieving a peak while the DTS always increased nonlinearly. The BTS was sensitive to T and c, while the DTS was mainly sensitive to T. The ratio of DTS to BTS first decreased with the increase of log(λ) and then increased instead from a minimum. It was found that the GBM with UDEC can well reproduce the uniaxial compression, direct tension and Brazilian tests of the Lac du Bonnet granite simultaneously only on condition that λ = 2.51. This indicated that the shear stiffness of the grain boundary in the Lac du Bonnet granite may be several times larger than its normal stiffness. This may be the main factor controlling the difference in the BTS and DTS of the Lac du Bonnet granite. [ABSTRACT FROM AUTHOR]

Asthma-COPD overlap (ACO) has been under intensive focus; however, the levels of damage-associated molecular patterns (DAMPs) that can activate the innate and adaptive immune responses of ACO are unknown. The present study aimed to examine the levels of some DAMPs in asthma, COPD, and ACO and to identify the associations between clinical characteristics and DAMPs in ACO. Sputum from subjects with asthma (n = 87) or COPD (n = 73) and ACO (n = 68) or from smokers (n = 62) and never-smokers (n = 62) was analyzed for high mobility group protein B1 (HMGB1), heat shock protein 70 (HSP70), LL-37, S100A8, and galectin-3 (Gal-3). The concentration of HMGB1, HSP70, LL-37, and S100A8 proteins in sputum from ACO patients was significantly elevated, whereas that of Gal-3 was reduced, compared to that of smokers and never-smokers. The levels of HMGB1 and Gal-3 proteins in ACO patients were elevated compared to those in asthma patients. The sputum from ACO patients showed an increase in the levels of LL-37 and S100A8 proteins compared to that of asthma patients, whereas the levels decreased compared to those of COPD patients. The concentrations of HMGB1, HSP70, LL-37, and S100A8 proteins in the sputum of 352 participants were negatively correlated, whereas the levels of Gal-3 were positively correlated, with FEV1, FEV1%pred, and FEV1/FVC. Sputum HMGB1 had a high AUC of the ROC curve while distinguishing ACO patients from asthma patients. Meanwhile, sputum LL-37 had a high AUC of the ROC curve in differentiating asthma and COPD. The release of sputum DAMPs in ACO may be involved in chronic airway inflammation in ACO; the sputum HMGB1 level might serve as a valuable biomarker for distinguishing ACO from asthma, and the sputum LL-37 level might be a biomarker for differentiating asthma and COPD. [ABSTRACT FROM AUTHOR]

Various studies report discordant results regarding the efficacy, parameters, and underlying mechanisms of repetitive transcranial magnetic stimulation (rTMS) combined with cognitive training (CT) on Alzheimer's disease (AD). The objective of the study was to assess the effect of rTMS-CT on cognition, the activities of daily life, neuropsychiatric behavioral symptoms, and metabolite levels beneath the stimulated areas of the brain in patients with AD and to investigate the correlation of metabolic changes (measured with proton magnetic resonance spectroscopy [1H-MRS]) with clinical outcomes after treatment. Thirty consecutive patients with mild or moderate AD were enrolled and randomly divided into one of the two intervention groups: (1) real rTMS with CT (i.e., real group) and (2) sham rTMS with CT (i.e., sham group). 10 Hz rTMS was used to stimulate the left dorsolateral prefrontal cortex (DLPFC) and then to stimulate the left lateral temporal lobe (LTL) for 20 min each day for 4 weeks. Each patient underwent neuropsychological assessment at baseline (T0), immediately after treatment (T1), and 4 weeks after treatment (T2). The ratios of N-acetylaspartate/creatine (NAA/Cr), myoinositol/creatine (mI/Cr), and choline/creatine (Cho/Cr) in the stimulated cortex were measured using 1H-MRS at T0 and T1. Twenty-eight patients were treated with rTMS-CT for 4 weeks. Two patients in the sham group withdrew after being treated several times. Compared with the sham group, the cognitive function and behavior in the real rTMS group improved significantly at T1 and T2. In the real group, compared with the sham group, the NAA/Cr ratio in the left DLPFC was significantly elevated (p = 0.045); however, in the left LTL, it only showed a tendency toward increase (p = 0.162). The change in the NAA/Cr ratio in the left DLPFC was negatively correlated with the change in the cognitive scales of the Alzheimer's Disease Assessment Scale (ADAS-cog). This study indicated a possible modest effect of rTMS-CT on preventing clinical and neuronal functional deterioration in the left DLPFC of patients with AD. The left DLPFC is a better candidate area than the left LTL. [ABSTRACT FROM AUTHOR]

Graphite was used as a solid lubricant to reduce thermal damage in diamond bit when drilling without coolant. Graphite was added to the bit matrix material to reduce friction coefficient and heat. The influence of content, granularity, and surface metallization of graphite on the mechanical property and dry friction properties of the matrix, as well as the effect of diamond lifetime in the working layer were studied. Results showed that the hardness, bending strength, and friction coefficient of matrix gradually decreased with the increase in graphite concentration. Meanwhile, the abrasion loss decreased first and then increased, and the lifetime of diamond in the working layer gradually increased. With the decrease in graphite granularity, the bending strength and friction coefficient of matrix gradually decreased, whereas the hardness, abrasion loss of matrix, and diamond lifetime in the working layer gradually increased. After surface metallization of graphite, the hardness, bending strength, friction coefficient, and abrasion loss of matrix increased, whereas the lifetime of diamond in the working layer decreased. This study lays a foundation for drilling without water. [ABSTRACT FROM AUTHOR]

This paper involves the use of a compliant ankle rehabilitation robot (CARR) for the treatment of drop foot. The robot has a bio-inspired design by employing four Festo Fluidic muscles (FFMs) that mimic skeletal muscles actuating three rotational degrees of freedom (DOFs). A trajectory tracking controller was developed in joint task space to track the predefined trajectory of the end effector. This controller was achieved by controlling individual FFM length based on inverse kinematics. Three patients with drop foot participated in a preliminary study to evaluate the potential of the CARR for clinical applications. Ankle stretching exercises along ankle dorsiflexion and plantarflexion (DP) were delivered for treating drop foot. All patients gave positive feedback in using this ankle robot for the treatment of drop foot, although some limitations exist. The proposed controller showed satisfactory accuracy in trajectory tracking, with all root mean square deviation (RMSD) values no greater than 0.0335 rad and normalized root mean square deviation (NRMSD) values less than 6.7%. These preliminary findings support the potentials of the CARR for clinical applications. Future work will investigate the effectiveness of the robot for treating drop foot on a large sample of subjects. [ABSTRACT FROM AUTHOR]

Phosphotungstic acidified titanium-zirconium dioxide catalysts with different loading of phosphotungstic acid (HPA) were synthesized by a precipitation-impregnation method. The phosphotungstic acidified solid acids were characterized by fourier transform infrared spectrometer (FT-IR), X-ray diffraction (XRD), ammonia temperature programmed desorption (NH3-TPD), X-ray photoelectron spectroscopy (XPS) and transmission electron microscope (TEM) techniques. And the catalytic performance of HPA/TiO2-ZrO2 was explored for glucose degradation to 5-hydroxymethylfurfural (5-HMF) in biphasic system, such as the loading of HPA, the molar ratio of TiO2 to ZrO2, reaction time, temperature, amount of catalyst, the volume ratio of VNaCl(aq)/VTHF and magnetic stirring speed. It was found that activity of the catalyst was related to the amount and density of acid site. The optimized yield of 51.3% for 5-HMF and the optimum conversion rate of 95.4% for glucose were achieved by 5% HPA/TiO2-ZrO2. Meanwhile, recycling performance of the catalyst was investigated. And the catalyst had good thermal stability, the yield of 5-HMF was 41.2% and the conversion rate of glucose remained at 85.4% after five cycles. [ABSTRACT FROM AUTHOR]

DIviding RECTangles (DIRECT) is an efficient and popular method in dealing with bound constrained optimization problems. However, DIRECT suffers from dimension curse, since its computational complexity soars when dimension increases. Besides, DIRECT also converges slowly when the objective function is flat. In this paper, we propose a coordinate DIRECT algorithm, which coincides with the spirits of other coordinate update algorithms. We transform the original problem into a series of sub-problems, where only one or several coordinates are selected to optimize and the rest keeps fixed. For each sub-problem, coordinately dividing the feasible domain enjoys low computational burden. Besides, we develop adaptive schemes to keep the efficiency and flexibility to tackle different functions. Specifically, we use block coordinate update, of which the size could be adaptively selected, and we also employ sequential quadratic programming to conduct the local search to efficiently accelerate the convergence even when the objective function is flat. With these techniques, the proposed algorithm achieves promising performance on both efficiency and accuracy in numerical experiments. [ABSTRACT FROM AUTHOR]

Polyacrylonitrile nanofiber cloth coated with graphene oxide was carbonized and activated to fabricate nitrogen- and oxygen-enriched porous carbon/graphene (NAC@Gr) sandwich-like composites. The influence of graphene coating on the microstructure, surface composition, and supercapacitive performance of the as-prepared composites was investigated. The results indicated that significantly enhanced energy storage capability can be achieved due to the high specific surface area, optimized pore structure, and surface functionality. The composites show both high gravimetric and volumetric specific capacitances, for example, 380 F g (178 F cm) at 0.1 A g in 6 M KOH and 228 F g (125 F cm) at 1 A g in 1 M TEABF/AN electrolyte. The assembled symmetric supercapacitors exhibit high energy density, high power density, excellent cycling stability, and high-rate performance. [ABSTRACT FROM AUTHOR]

In order to control the effects of outliers in training data and get sparse results, Huang et al. (J Mach Learn Res 15:2185-2211, 2014) proposed the ramp loss linear programming support vector machine. This combination of $$\mathrm {l}_1$$ regularization and ramp loss does not only lead to the sparsity of parameters in decision functions, but also limits the effects of outliers with a maximal penalty. However, due to its non-convexity, the computational cost to achieve a satisfying solution is often expensive. In this paper, we propose a modified coordinate descent algorithm, which deals with a series of one-variable piecewise linear subproblems. Considering that the obtained subproblems are DC programming problems, we linearize the concave part of the objective functions and solve the obtained convex problems. To test the performances of the proposed algorithm, numerical experiments have been carried out and analysed on benchmark data sets. To enhance the sparsity and robustness, the experiments are initialized from C-SVM solutions. The results confirm its excellent performances in classification accuracy, robustness and efficiency in computation. [ABSTRACT FROM AUTHOR]

Aims/hypothesis: Glucokinase regulatory protein gene ( GCKR) variant rs780092 is a novel genetic variant associated with serum triacylglycerol (TG) identified in a genome-wide association study in East Asians. We aimed to investigate associations of rs780092 with incident type 2 diabetes and dyslipidaemia, and the longitudinal changes in glucose and lipid levels. Methods: A community-based prospective cohort study was conducted at baseline in 2008, including 5,613 non-diabetic participants (37% male, mean age 57.6 years) with 5 years of follow-up. Blood glucose and lipid was measured at baseline and follow-up. Results: Each rs780092 T-allele was associated with a 17% lower risk of incident type 2 diabetes (HR 0.83 [95% CI 0.73, 0.95]) and 36% higher risk of incident hypertriacylglycerolaemia (OR 1.36 [95% CI 1.08, 1.72]), after adjustment for baseline fasting glucose and TG and other confounders. The T-allele was associated with a 5 year increasing level of log TG (β ± SE, 0.01 ± 0.004, p = 0.005). Mediation analysis showed that both baseline TG and the 5 year increase in log TG were significant mediators in the associations of rs780092 with risk of diabetes. The risk of incident type 2 diabetes associated with 1 SD increase in total and LDL-cholesterol was 35% and 22% lower in TT carriers compared with CC carriers, respectively (both p for interaction ≤ 0.04). Conclusions/interpretation: The GCKR rs780092 variant showed opposite-directional associations with type 2 diabetes and hypertriacylglycerolaemia in a Chinese population. Both baseline level and 5 year change in serum TG were mediators of the association between the genetic variant and type 2 diabetes. [ABSTRACT FROM AUTHOR]

Age-related changes of resting state in default mode network (DMN) may provide new clues to the developing mechanism of normal brain as well as early diagnosis and therapy of some neuropsychiatric disorders. The application of multifractal theory to functional magnetic resonance imaging (fMRI) signals has recently raised increasing attention. We aim to explore the multifractal characteristics underlying the resting state functional magnetic resonance imaging (rs-fMRI) series extracted from DMN, and two issues are mainly discussed: (1) whether there exist multifractals in rs-fMRI series; (2) whether it is possible to distinguish between the different ages or genders by means of multifractal characteristics. Results demonstrated the existence of multifractals in rs-fMRI series in DMN. In addition, slight differences between young subjects and middle-aged or elderly subjects can be successfully detected by $$ \Delta_{\text{as}} \alpha $$ , a modified measure we proposed. Furthermore, it is revealed that the rs-fMRI series from young subjects possess smaller averaged scale index and weaker long range correlation, while those from middle-aged or elderly people present increasing averaged scale index and stronger long range correlation. Whereas no significant statistical differences has been found between male and female group. Our results, therefore, highlight the potential usefulness of multifractal analysis in fMRI series of a certain brain region, and provide important insights into healthy aging in DMN. [ABSTRACT FROM AUTHOR]

The quantile regression problem is considered by learning schemes based on ℓ-regularization and Gaussian kernels. The purpose of this paper is to present concentration estimates for the algorithms. Our analysis shows that the convergence behavior of ℓ-quantile regression with Gaussian kernels is almost the same as that of the RKHS-based learning schemes. Furthermore, the previous analysis for kernel-based quantile regression usually requires that the output sample values are uniformly bounded, which excludes the common case with Gaussian noise. Our error analysis presented in this paper can give satisfactory convergence rates even for unbounded sampling processes. Besides, numerical experiments are given which support the theoretical results. [ABSTRACT FROM AUTHOR]

Experiments were conducted to study the relationship between the transmission ratio (TR) and normal stress, joint roughness, joint number and frequency of incident waves, respectively, when ultrasonic waves pass across a rock mass with one joint and multiple parallel joints oriented normally. The ultrasonic waves were generated and received by pairs of piezoelectric transducers and recorded by an ultrasonic detector. The specimens were subjected to normal stress by a hydraulic jack and loading frame. The jointed rock mass was produced by superposing rock blocks in the study. Rough joints were produced by grooving notches on the planar joints formed by sawing directly. In the case of multiple parallel joints, the overall thickness of specimens was maintained while the joint number changed. Three pairs of P-wave transducers and one pair of S-wave transducers with different frequencies were, respectively, applied and all transducers emitted signals perpendicular to the joints in the experiment. The results indicate that TR increases with increasing normal stress while the increment rate decreases gradually. This is particularly so when the normal stress is high enough that TR will approximate 1 even if the rock mass has many joints. In addition, the experiments indicate that the higher the wave's frequency, the lower its TR, and this phenomenon is gradually reduced as the normal stress increases. In response to S-waves, TR increases with increase in joint roughness; however, in response to P-waves, TR decreases gradually with increase in joint roughness. For multiple parallel joints in a fixed thickness rock mass with normally incident P-waves, TR does not always decrease with increase in the number of joints, and there is a threshold joint spacing for a certain incident wave: when the joint spacing is smaller than the threshold value, TR will increase with a decrease in joint spacing. The experimental results support similar conclusions based on analytical results drawn by Cai and Zhao (Int J Rock Mech Min Sci 37(4):661-682, ), Zhao et al. (Int J Rock Mech Min Sci 43(5):776-788, ) and Zhu et al. (J Appl Geophys 73:283-288, ). [ABSTRACT FROM AUTHOR]

Utilizing compact representations for continuous piecewise linear functions, this paper discusses some theoretical properties for nonseparable continuous piecewise linear programming. The existence of exact penalty for continuous piecewise linear programming is proved, which allows us to concentrate on unconstrained problems. For unconstrained problems, we give a sufficient and necessary local optimality condition, which is based on a model with universal representation capability and hence applicable to arbitrary continuous piecewise linear programming. From the gained optimality condition, an algorithm is proposed and evaluated by numerical experiments, where the theoretical properties are illustrated as well. [ABSTRACT FROM AUTHOR]

This paper considers parameter estimation for nonlinear model using median squared error (MSE) criterion, which is limited to linear model in the past. It is shown that applying MSE, the essence of estimating parameters for hinging hyperplanes (HH) and linear model are the same. Motivated by this fact, MSE estimation is discussed for HH. A local optimality condition is given and based on this condition, an algorithm using linear programming technique is proposed. Numerical experiments show the good performance of the proposed estimation strategy and algorithm. [ABSTRACT FROM AUTHOR]