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Restoring high quality images from raw data in low light is challenging due to various noises caused by limited photon count and complicated Image Signal Process (ISP). Although several restoration and enhancement approaches are proposed, they may fail in extreme conditions, such as imaging short exposure raw data. The first path-breaking attempt is to utilize the connection between a pair of short and long exposure raw data and outputs RGB images as the final results. However, the whole pipeline still suffers from some blurs and color distortion. To overcome those difficulties, we propose an end-to-end network that contains two effective subnets to joint demosaic and denoise low exposure raw images. While traditional ISP are difficult to image them in acceptable conditions, the short exposure raw images can be better restored and enhanced by our model. For denoising, the proposed Short2Long raw restoration subnet outputs pseudo long exposure raw data with little noisy points. Then for demosaicing, the proposed Color consistent RGB enhancement subnet generates corresponding RGB images with the desired attributes: sharpness, color vividness, good contrast and little noise. By training the network in an end-to-end manner, our method avoids additional tuning by experts. We conduct experiments to reveal good results on three raw data datasets. We also illustrate the effectiveness of each module and the well generalization ability of this model. • We propose a Short2Long raw restoration strategy to process low quality raw images and restore pseudo raw ones for the subsequent subnet. It extracts sufficient information and removes enough noisy points, thus mainly focuses on the denoising task. • We device a Color consistent RGB enhancement mechanism to rearrange raw images and generate the final RGB outputs. With the residual connection and channel-wise attention, it reconstructs the color spatial information and emphasizes more on the demosaicing task. • Both quantitative and qualitative experiments are conducted to demonstrate the superiority of our proposed method. Ablation studies prove the effectiveness of modules. We also illustrate its promising generalization ability on unseen raw data such as images from smartphones. [ABSTRACT FROM AUTHOR]

LiNi 0.8 Co 0.15 Al 0.05 O 2-δ (NCAL) has been demonstrated to be an excellent electrode with dual catalytic activities of hydrogen oxidation reaction (HOR) and oxygen reduction reaction (ORR) for solid oxide fuel cells (SOFCs). Reports have indicated that the anode NCAL tends to be reduced during cell operation and produce LiOH and Li 2 CO 3. In this work, the effect of the online reaction byproducts of NCAL electrodes, LiOH and Li 2 CO 3 , on the performance of SOFCs is investigated. Different amounts of LiOH and Li 2 CO 3 are separately added to the Ce 0.8 Sm 0.2 O 2-δ (SDC) electrolyte for fabricating SOFCs with NCAL electrodes. The power output under normal and reverse operation is studied for the cells with lithium salt addition from 5 wt% to 30 wt%. Electrochemical impedance spectroscopy (EIS) and distribution of relaxation times (DRT) analysis suggested that the addition of LiOH or Li 2 CO 3 to the SDC reduces HOR and ORR activities of the cells, leading to lower cell performance. The cross-sectional SEM of the cells shows that the added LiOH and Li 2 CO 3 makes the electrolyte porous and densifies the electrode, which is the main reason for the reduction of cell performance. In addition, the porosity of electrolyte is modified during cell fabrication in order to construct flowing pathways for the online reaction byproducts of NCAL electrode to move from electrode to electrolyte, resulting in optimized cell performance. This study provides an insight into facilitating the performance of NCAL electrode-based SOFC. [Display omitted] • Adding LiOH and Li 2 CO 3 in the electrolyte is unfavorable for NCAL electrode fuel cell. • LiOH and Li 2 CO 3 reduce electrode performance from DRT analysis but can improve electrolyte performance. • Constructing porosity helps improve both electrolyte and electrode performance. [ABSTRACT FROM AUTHOR]

Open-world instance segmentation has recently gained significant popularity due to its importance in many real-world applications, such as autonomous driving, robot perception, and remote sensing. However, previous methods have either produced unsatisfactory results or relied on complex systems and paradigms. We wonder if there is a simple way to obtain state-of-the-art results. Fortunately, we have identified two observations that help us achieve the best of both worlds: (1) query-based methods demonstrate superiority over dense proposal-based methods in open-world instance segmentation, and (2) learning localization cues is sufficient for open-world instance segmentation. Based on these observations, we propose a simple query-based method named OpenInst for open-world instance segmentation. OpenInst leverages advanced query-based methods like QueryInst and focuses on learning localization cues. Notably, OpenInst is an extremely simple and straightforward framework without any auxiliary modules or post-processing, yet achieves state-of-the-art results on multiple benchmarks. Specifically, in the COCO → UVO scenario, OpenInst achieves a mask Average Recall (AR) of 53.3, outperforming the previous best methods by 2.0 AR with a simpler structure. We hope that OpenInst can serve as a solid baseline for future research in this area. The source codes are available at https://github.com/hustvl/OpenInst. • OpenInst achieves state-of-the-art results on multiple datasets. Our study confirms that incorporating box IoU into query-based detectors improves their generalizability. • OpenInst is the first work that achieves both simplicity and high-performance, serving as a solid baseline for future research in the open-world community. • We conduct extensive ablation studies to analyze each component used in our model. We hope those observations benefit future researches in this area. [ABSTRACT FROM AUTHOR]

• First attempts to model soft machines driven by buckling actuators. • Simulation provides missing information vital for real designs. • Results aid the design and control of soft machines. Buckling of elastomeric materials is recoverable and can be harnessed to provide useful functions. Soft machines enabled by buckling actuators have been demonstrated experimentally, while no efforts have been conducted to model these actuators and machines numerically. This paper fills this blank and presents numerical modelling of buckling actuators and the derived soft machines. Key design parameters are obtained through the simulation, which are missing and typically difficult to be obtained in experiment. The numerical results are helpful to understanding the working mechanism of buckling actuators, and shed light on design and control of soft machines enabled by buckling actuators. The idea and the strategy can be developed further for the design of other soft machines. [ABSTRACT FROM AUTHOR]

• The activity modeling method based on the emergent paradigm and the directed-weighted network can fully extract feature structure. • The additional context-aware information of each whole activity settles the issue of activity ambiguity. • The heterogeneous mechanism of pheromone keeps the balance between the new and old context-aware information. With the population aging, elderly health monitoring is triggering more studies on daily activity recognition as the fundamental of ambient assisted living. It is remarkable that activity recognition remains difficulties including how to adequately extract feature structure and settle the issue of activity confusion. To address these challenges, we propose a novel activity modeling method under the emergent paradigm with marker-based stigmergy and the directed-weighted network with additional context-aware information. In the modeling process, stigmergy is first introduced to aggregate the context information at the low level for generating activity pheromone trails, and then the constructed stigmergic trails are represented in form of directed-weighted network with distinguishability of individual pheromone source corresponding to location. The potential advantage is that the robust trails with distinguishable individual initial positions are feasible to supplement user's daily habits and thus both inter-class and intra-class distances can be kept at acceptable levels. Experiments on Aruba demonstrates that the proposed emergent modeling method can effectively deal with the problems of feature extraction and activity ambiguity and achieve good classification performance. [ABSTRACT FROM AUTHOR]

This paper proposes a novel rotation invariant feature for object recognition. Firstly, the local Fourier transform features of pixels in the described region are encoded by Fisher Vectors. Then, the encoded vectors are aggregated into a final representation by ordinal pyramid pooling, which hierarchically partitions the described region into sub-regions based on the orders of its pixels’ rotation invariants. Since both the encoded Fisher Vectors and the ordinal pyramid pooling strategy are rotation invariant, the extracted feature is rotation invariant by nature. Two kinds of rotation invariants are investigated in this framework, one is the Radial Gradient Orientation and the other is the Radial Gradient Angle. Experiments on handwritten digit recognition and airplane/car detection in aerial images demonstrate the effectiveness of the proposed method, which outperforms the state of the art. [ABSTRACT FROM AUTHOR]

The photoionization cross sections of the excited levels (3s3p P 0 , 1 , 2 o 3 ) of atomic Mg have been studied theoretically using both the nonrelativistic and fully relativistic R -matrix method. For the threshold cross sections, as previous nonrelativistic studies, present calculations show significant differences (a factor of 3) from former experimental values. Large discrepancies with experiment calls for additional measurements of the photoionization cross sections from the excited states of Mg. [ABSTRACT FROM AUTHOR]

7-Aminocoumarins are commonly used as fluorophores for application in molecular monitoring, cell imaging and many other fields. Herein, a series of fluorescent 7-aminocoumarins were prepared via Er(OTf) 3 -catalyzed Pechmann condensation of 3-aminophenols with β-ketoesters in 19–96% yields. Among them, 7-(dimethylamino)-4-(pyridin-4-yl)-2H-chromen-2-one (3j) displayed a fluorescence maximum with a wavelength of 557 nm and a large Stokes shift of 166 nm in DMSO, and showed strong fluorescence in sub acid to alkaline environment. Besides, 3j exhibited excellent photo stability and stable fluorescence intensity in the presence of some metal cations and biomolecules in neutral solution. A series of fluorescent 7-aminocoumarins were prepared via Er(OTf) 3 -catalyzed Pechmann condensation of 3-aminophenols with β-ketoesters. Among them, 7-(dimethylamino)-4-(pyridin-4-yl)-2H-chromen-2-one (3j) exhibited excellent photophysical properties, and displayed strong fluorescence in sub acid to alkaline environment. [Display omitted] • An efficient approach to access fluorescent 7-aminocoumarins •Easy work-up and broad substrate scopes •Excellent fluorescence properties [ABSTRACT FROM AUTHOR]

Neuronal dendrites and dendritic spines are essential for normal synaptic transmission and may be critically involved in the pathophysiology of various neurological disorders, including depression. Emerging data supports the role of mitochondria in dendritic protrusions in modulating the development and morphological plasticity of spines. Mitophagy, a mitochondria-specific form of autophagy, is the fundamental process of clearing damaged mitochondria to maintain cellular homeostasis. As a brain-specific microRNA, miR-134 is localized to the synaptodendritic compartment of hippocampal neurons and negatively regulates the development of dendritic spines. However, the role of miR-134 in mitophagy related to dendritic deficits in the pathophysiology of depression remains unclear. In this study, we showed that miR-134-5p knockdown abrogated depression-like behavioral symptoms and corrected aberrant spine morphology in hippocampal neurons of chronic unpredictable mild stress (CUMS) mice. Moreover, knockdown of miR-134-5p triggered autophagy in dendrites, improved mitochondrial impairment, and induced the generation of autophagosomes in the hippocampus of CUMS mice. We further found that AMP-activated protein kinase (AMPK), which mediates the impairment of defective mitochondria via mitophagy, can bind directly to miR-134-5p and is negatively regulated by this miRNA. This study demonstrates that miR-134-5p exerts an enormous effect on dendritic deficits by promoting AMPK-mediated mitophagy and provides a potential new target for antidepressant drug research and development. [Display omitted] • CUMS induced depression-like behavior is accompanied by hippocampal neuron damage and dendritic spine reduction. • Knockdown of miR-134-5p improved depression-like behavior and hippocampal dendritic spine morphology in CUMS mice. • Knockdown of miR-134-5p activated mitophagy in the hippocampal dendrites of CUMS mice. • Knockdown of miR-134-5p rescued hippocampal dendritic spine anomalies by targeting AMPK-mediated mitophagy. [ABSTRACT FROM AUTHOR]

• We are the first to explore the uncertainty of hashing bits during approximate optimization. Depending on the magnitude of uncertainty, the corresponding hashing bits and input images receive different attention. • We propose to explicitly model bit-level and image-level uncertainty, resorting to the output discrepancy between the hashing network and the momentum-updated network. • Extensive experiments on the CIFAR-10, the NUS-WIDE, the MS-COCO, and the largescale Clothing1M datasets demonstrate that our method significantly improves retrieval performance when compared with state-of-the-art methods. Combinatorial optimization (CO) has been a hot research topic because of its theoretic and practical importance. As a classic CO problem, deep hashing aims to find an optimal code for each data from finite discrete possibilities, while the discrete nature brings a big challenge to the optimization process. Previous methods usually mitigate this challenge by binary approximation, substituting binary codes for real-values via activation functions or regularizations. However, such approximation leads to uncertainty between real-values and binary ones, degrading retrieval performance. In this paper, we propose a novel Deep Momentum Uncertainty Hashing (DMUH). It explicitly estimates the uncertainty during training and leverages the uncertainty information to guide the approximation process. Specifically, we model bit-level uncertainty via measuring the discrepancy between the output of a hashing network and that of a momentum-updated network. The discrepancy of each bit indicates the uncertainty of the hashing network to the approximate output of that bit. Meanwhile, the mean discrepancy of all bits in a hashing code can be regarded as image-level uncertainty. It embodies the uncertainty of the hashing network to the corresponding input image. The hashing bit and image with higher uncertainty are paid more attention during optimization. To the best of our knowledge, this is the first work to study the uncertainty in hashing bits. Extensive experiments are conducted on four datasets to verify the superiority of our method, including CIFAR-10, NUS-WIDE, MS-COCO, and a million-scale dataset Clothing1M. Our method achieves the best performance on all of the datasets and surpasses existing state-of-the-art methods by a large margin. [ABSTRACT FROM AUTHOR]

• Estrogen receptor α deficiency produced a depression-like effect in the tail suspension test and forced swimming test of female mice. • Estrogen receptor α deficiency affected cardiac function by aggravating cardiomyocyte disorders of female mice. • Estrogen receptor α deficiency simultaneously influenced BDNF-AKT/ERK1/2 signaling in the hippocampus and heart of female mice. • Quercetin alleviated ERα-/--induced depression-like responses and cardiac dysfunction through BDNF-TrkB-AKT and ERK1/2 signaling. Brain-derived neurotrophic factor (BDNF) is the potential link between depression and cardiovascular disease and estrogen receptor α (ERα), an estrogen-mediated major regulator, plays an important role in protecting against depression and cardiovascular disease. However, the relationship between BDNF and ERα remains obscure. Herein, quercetin (QUE), a kind of plant flavonoids and existed in many vegetables and fruits, was found to simultaneously reverse ERα−/−-induced depression-like and cardiac dysfunction by reducing immobility time in the tail suspension test (TST) and forced swimming test (FST), and decreasing systolic blood pressure and activating the apoptosis-related proteins, BDNF, tropomyosin-related kinase B (TrkB), protein kinase B (AKT), and extracellular regulatory protein kinase (ERK1/2) in the hippocampal and cardiac tissues of female mice. These findings suggested that ERα might be involved in the regulation of BDNF activity, thereby regulating depression-like and cardiovascular responses in female mice, and QUE exerted significant antidepressant and cardioprotective effects, at least in part, through BDNF-TrkB-AKT/ERK1/2 to effectively inhibit ERα−/−-induced hippocampal and cardiac dysfunction. [ABSTRACT FROM AUTHOR]

With the acceleration of aging process of population structure, the single resident lifestyle is increasing on account of the high cost of care services and the privacy invasion concern. It is essential to monitor the activities of solitary elderly to find the emergency and lifestyle deviation, as independent life cannot be maintained due to physical or mental problems. The unobtrusive systems are the most preferred choice for the real-life long-term monitoring, while the camera and wearable devices based systems are not suitable due to the privacy and uncomfortableness, respectively. We propose a novel sensor-based activity recognition model based on the two-layer multi-granularity framework and the emergent paradigm with marker-based stigmergy. The stigmergy based marking subsystem builds features by aggregating the context-aware information and generating the two-dimensional activity pheromone trail. The two-layer framework consists of coarse-grained and fine-grained classification subsystems. The coarse-grained subsystem identifies whether the input completed activity segmented by the traditional method is easily-confused, and utilizes our generalized segmentation method to increase the inter-cluster distance. The fine-grained subsystem employs machine learning or deep learning classifiers to realize the activity recognition task. The proposed model is a data-driven model based on the information self-organization. It does not need sophisticated domain knowledge, and can fully mine the hidden feature structure containing semantically related information and spatio-temporal characteristics. The experimental results demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Currently, there is no universally accepted standard treatment for ocular myasthenia gravis (OMG) in children. We aimed to investigate the possible proper regimens and timing of treatment for pediatric OMG cases based on the clinical manifestations: OMG with ptosis only and OMG with other features. One hundred and forty two OMG cases attended at the Department of Pediatrics, Xiangya Hospital, Central South University, from 2010 to 2019 were included, and information from medical records was reviewed and recorded. Comparisons of clinical characteristics between patients with OMG with ptosis only and patients with OMG with other features as well as between patients treated with glucocorticoid (GC) within or after six months from disease onset were performed. OMG with other features constituted about 54.9% of the cases, and 66.2% of the patients achieved optimal outcome. Patients with OMG with ptosis only responded to pyridostigmine alone more than patients with OMG with other features who required several therapies (P < 0.001). Patients with OMG with ptosis only had a larger proportion of optimal outcome than the patients with OMG with other features (P = 0.002), and the difference remained significant even when the individual outcome groups were compared (P < 0.001). Patients who received GC within six months had a greater proportion of optimal outcome than those who received it after six months (P < 0.001). Although OMG with other features is a more common subtype of OMG, it is also more severe than OMG with ptosis only. An earlier addition of GC leads to optimal outcome. [ABSTRACT FROM AUTHOR]

The traditional Chinese medicine (TCM) Rehmanniae Radix (RR) refers to the fresh or dried root tuber of the plant Rehmannia glutinosa Libosch of the family Scrophulariaceae. As a traditional Chinese herbal medicine (CHM), it possesses multiple effects, including analgesia, sedation, anti-inflammation, antioxidation, anti-tumor, immunomodulation, cardiovascular and cerebrovascular regulation, and nerve damage repair, and it has been widely used in clinical practice. In recent years, scientists have extensively studied the active components and pharmacological effects of RR. Active ingredients mainly include iridoid glycosides (such as catalpol and aucuboside), phenylpropanoid glycosides (such as acteoside), other saccharides, and unsaturated fatty acids. In addition, the Chinese patent medicine (CPM) and Chinese decoction related to RR have also become major research subjects for TCM practitioners; one example is the Bolus of Six Drugs, which includes Rehmannia, Lily Bulb and Rehmannia Decoction, and Siwu Decoction. This article reviews recent literature on RR; summarizes the studies on its chemical constituents, pharmacological effects, and clinical applications; and analyzes the progress and limitations of current investigations to provide reference for further exploration and development of RR. [Display omitted] • Rehmanniae Radix possesses multiple effects, including antioxidation and anti-tumor. • Its active ingredients mainly include iridoid and phenylpropanoid glycosides. • Chinese decoctions related to Rehmanniae Radix are widely used in clinical practice. [ABSTRACT FROM AUTHOR]

SLIT2 is a candidate tumor suppressor gene and recent studies have shown that SLIT2 expression is suppressed or reduced by hypermethylation in the promoter region in various cancers. The aim of this study was to investigate the association between SLIT2 promoter methylation and nasopharyngeal carcinoma (NPC) and its relative diagnostic ability for NPC. Bisulfite pyrosequencing technology was performed to measure methylation levels of the SLIT2 promoter in tissue and plasma samples from 61 NPC patients and 38 normal volunteers. The receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to evaluate the diagnostic ability of SLIT2 methylation for diagnosing NPC. Our results showed that methylation levels of the SLIT2 promoter were significantly higher in NPC patients compared with individuals, both in tissue samples ( P = 2.57E − 10) and plasma samples (plasma: P = 3.86E − 13). In addition, the frequency of SLIT2 promoter methylation markedly increased in the advanced stage (tissue: P = 3.50E − 05; plasma: P = 1.14E − 04) and advanced T classified (tissue: P = 9.00E − 06; plasma: P = 3.80E − 05), as well as in lymph node metastasis patients (tissue: P = 1.82E − 03; plasma: P = 2.22E − 03). In addition, the AUCs according to tissue and plasma samples were 0.846 and 0.866, respectively. When these two sample-types were combined, the AUC increased slightly to 0.874. Our study revealed that elevated SLIT2 promoter methylation contributed to the risk of NPC, as well as being involved in its progression and metastasis. Therefore, the methylated SLIT2 promoter could serve as a potential biomarker for diagnosing NPC. [ABSTRACT FROM AUTHOR]

Chronic atrophic gastritis (CAG) is a global digestive system disease and one of the important causes of gastric cancer. The incidence of CAG has been increasing yearly worldwide. This article reviews the latest research on the common causes and future therapeutic targets of CAG as well as the pharmacological effects of corresponding clinical drugs. We provide a detailed theoretical basis for further research on possible methods for the treatment of CAG and reversal of the CAG process. CAG often develops from chronic gastritis, and its main pathological manifestation is atrophy of the gastric mucosa, which can develop into gastric cancer. The drug treatment of CAG can be divided into agents that regulate gastric acid secretion, eradicate Helicobacter. pylori (H. pylori) , protect gastric mucous membrane, or inhibit inflammatory factors according to their mechanism of action. Although there are limited specific drugs for the treatment of CAG, progress is being made in defining the pathogenesis and therapeutic targets of the disease. Growing evidence shows that NF-κB, PI3K/AKT, Wnt/ β-catenin, MAPK, Toll-like receptors (TLRs), Hedgehog, and VEGF signaling pathways play an important role in the development of CAG. [Display omitted] • Chronic atrophic gastritis (CAG) is one of the commonest digestive diseases worldwide. • Drugs for CAG include proton pump inhibitors, H2 receptor antagonists, gastric mucosal protectants, and others. • NF-κB, PI3K/AKT, Wnt/β-catenin, MAPK, TLRs, Hedgehog and VEGF signaling pathways play an important role in CAG. [ABSTRACT FROM AUTHOR]

Heterostructure materials deliver special properties comparing with single phase materials. In this study, the performance of Na 0.5 Bi 0.5 TiO 3 (NBT) electrolyte fuel cell is proved to be optimized by constructing heterostructures with other materials. SOFC based on NBT single phase electrolyte exhibits poor stability and low power output. By mixing NBT with electronic conductor La 0.6 Sr 0.4 Co 0.2 Fe 0.8 O 3 (LSCF), improved performance is obtained and power output is observed to be dependent on the weight ratio of NBT to LSCF. It is interesting that the best performance is obtained in the cell with an optimized weight ratio of 30 wt% NBT - 70 wt% LSCF, in which the amount of electronic conductor exceeds that of ionic conductor. However, the stability of SOFC based on NBT-LSCF composite electrolyte still needs to be improved. In addition, the composition of sodium carbonate and lithium carbonate is added to the NBT-LSCF composite electrolyte for the purpose of creating amorphous shells around the NBT-LSCF particles, which is expected to protect the NBT-LSCF particles from reducing by hydrogen. Improved stability of the cell is then observed. This study provides an effective way to enhance the ionic conductivity and stability of electrolyte by constructing heterostructures. [ABSTRACT FROM AUTHOR]

Abstract: This paper concerns the issue of the maximum-likelihood estimation (MLE) for the concentration parameters of the von Mises–Fisher (vMF) distributions, which are crucial to directional data analysis. In particular, we study the numerical approximation approach for solving the implicit nonlinear equation arising from building the MLE of the concentration parameter of vMF distributions. In addition, we address the implementation of , the modified Bessel function of the first kind, which is the most time-consuming and fundamental ingredient in the proposed approximation scheme of the MLE for . The main contribution of this paper is two fold. The first is to present a two-steps Halley based method for exploring a high-order approximation of the MLE for , which can significantly contribute to the improvement of estimation accuracy. The second is to develop a novel approach for the implementation of , which can make the substantial improvement of computation efficiency for computing the MLE approximation for . The numerical experiments were conducted to compare the proposed schemes with those in the existing works by Tanabe et al. and Sra . The experimental results show that, given the same amount of computation as their methods, the proposed high-order scheme can achieve much more accurate approximations while our implementation of is preferable yet desirable for high dimensional applications. [Copyright &y& Elsevier]

Pore pressures in the Xujiahe gas-bearing formations are highly overpressured in the western Sichuan basin. The abnormally high overpressure and strong tectonic stress cause very high horizontal stresses. The high in-situ stresses, tectonic stress regimes, and tight formations severely impact development and production of the Xujiahe tight sandstone reservoirs. Overpressure generation mechanisms are analyzed based on measured data in several dozen wells in the studied gas fields. It is found that the sonic or seismic transit time can be used to predict pore pressure. Two major reservoirs (Xu2 and Xu4) belong to different fluid compartments with distinct pore pressure gradients. The Xu4 has a much higher pore pressure gradient (20 MPa/km) than the Xu2 (15.6 MPa/km). Measured data from hydraulic fracturing tests and borehole image logs in vertical wells are analyzed. The results show that the minimum horizontal stress gradient in the Xu4 reservoir reaches as high as 24 MPa/km, close to the overburden gradient. The Xu2 reservoir has a slightly lower minimum horizontal stress gradient. The high minimum horizontal stress and high rock strength cause abnormally high formation breakdown pressure gradient (24.8–34 MPa/km). The high breakdown pressure, high propagation pressure, and unfavorable stress regime result in a great difficulty for the reservoir stimulation. One of the major impacts is that hydraulic fracturing operations can only create very short hydraulic fractures, which markedly limits reservoir productivity. Based on field measurements, in-situ stress determination and assessment are given, and a new method for horizontal stress estimation is proposed. Accordingly, reliable prediction of formation breakdown and propagation pressures are proposed, which are more suitable for the tight reservoirs. Recommendations are given for effective development of the tight reservoirs with impacts of high in-situ stresses. Image 1 • Impact and mechanism of in-situ stresses and strong tectonics are studied for hydraulic fracturing in tight sandstone reservoirs. • Overpressure and tectonic stress cause very high horizontal stresses and induce extremely high breakdown pressure. • Pore pressure prediction and horizontal stress estimation methods are proposed. • New methods of formation breakdown and fracture propagation pressures are obtained for tight reservoirs. • Recommendations are given for effective development of the tight and high in-situ stress reservoirs. [ABSTRACT FROM AUTHOR]

Mineral surface is a pivotal place for interactions between minerals and other materials and is helpful to be quantitatively characterized with the aid of measuring the mineral surface area (MSA) by ethylene glycol monoethyl ether (EGME) adsorption. However, in fine-grained sediments, the existence of organic matter (OM) may impede the accuracy of their EGME MSA measurement. This study selected mudrocks with type-I and type-III OM and separated their OMs, which were subjected to total organic carbon content (TOC) and EGME adsorption measurement to investigate the influence of OM on MSA measurement of mudrock by EGME adsorption. The results show that OM has a remarkable contribution to EGME specific surface area (EGME SSA) of mudrocks, and the contribution from type-I OM is greater than type-III OM. The contribution rate of OM to EGME SSA of mudrocks is exponentially correlated with TOC and EGME SSA of mudrocks, indicating that different influential extents of OM to EGME MSA of mudrocks depend on its TOC and EGME retention capacity. By mathematical extrapolation, mudrocks with TOC < 1.5 wt% or EGME SSA > 100 m2/g is recommended to be available for EGME adsorption to measure MSA of mudrock. Otherwise, OM removal of mudrock sample has to be performed prior to employing EGME adsorption. This study discusses the contribution of OM to EGME SSA of mudrocks and provides two measures to judge the validity of EGME adsorption for MSA measurement of mudrocks, which is helpful to sample preparation for EGME adsorption and identify the availability of EGME MSA. • Organic matter (OM) can contribute to the ethylene glycol monoethyl ether specific surface area (EGME SSA) of mudrock. • The contribution of OM to EGME SSA of mudrock is greater in type-I OM than type-III OM. • TOC < 1.5 wt% or EGME SSA > 100 m2/g is recommended when employing EGME adsorption for mineral surface area of mudrock. [ABSTRACT FROM AUTHOR]

Abstract This paper concerns the issue of monitoring elderly behavior in the context of ambient assisted living (AAL). Under the framework of online daily habit modeling (ODHM), we employ the emergent representation for activities of daily living (ADLs) with position-based stigmergy, and then combine it with convolution neural networks (CNNs) to accomplish the tasks of recognizing ADLs. In addition, we propose a new paradigm of activity summarization with the robustness to break interruptions. Radio tomographic imaging (RTI) is promoted as a simple yet flexible way of facilitating the required position-based stigmergy. Such position-based AAL systems can benefit the advantages of having no need any sophisticated domain models in analyzing and understanding ADLs while no burden training is involved in ODHM. Moreover, the emergent based data aggregation and deep learning of CNN together allow the recognition of ADLs at a fine-grained level, which contributes to the performance improvement of ODHM. Experimental results demonstrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

• Decoupling of the effects of bubble desorption and mass transfer enhancement. • Nanopore-expansion and promoted AAO growth efficiency through bubble desorption and ion migration. • Inhibition of mass transfer and decrease in efficiency caused by jet cavitation-induced nanopore contraction. Ultrasound has been proven to enhance the mass transfer process and impact the fabrication of anodic aluminum oxide (AAO). However, the different effects of ultrasound propagating in different media make the specific target and process of ultrasound in AAO remain unclear, and the effects of ultrasound on AAO reported in previous studies are contradictory. These uncertainties have greatly limited the application of ultrasonic-assisted anodization (UAA) in practice. In this study, the bubble desorption and mass transfer enhancement effects were decoupled based on an anodizing system with focused ultrasound, such that the dual effects of ultrasound on different targets were distinguished. The results showed that ultrasound has the dual effects on AAO fabrication. Specifically, ultrasound focused on the anode has a nanopore-expansion effect on AAO, leading to a 12.24 % improvement in fabrication efficiency. This was attributed to the promotion of interfacial ion migration through ultrasonic-induced high-frequency vibrational bubble desorption. However, AAO nanopores were observed to shrink when ultrasound was focused on the electrolyte, accompanied by a 25.85 % reduction in fabrication efficiency. The effects of ultrasound on mass transfer through jet cavitation appeared to be the reason for this phenomenon. This study resolved the paradoxical phenomena of UAA in previous studies and is expected to guide AAO application in electrochemistry and surface treatments. [ABSTRACT FROM AUTHOR]