Miracle-dz/UniFAR-FTUs huggingface dataset:
MDRSteg: large-capacity image steganography based on multi-scale dilated ResNet and combined chi-square distance loss

Abstract. Image steganography has emerged as a method of hiding secret data within an image file to ensure the security of the transmitted data. In this study, we propose an architecture named MDRSteg to unobtrusively hide a large-size image in another image based on a residual neural network with dilated convolution and multi-scale fusion. The architecture consists of an embedding network to hide the secret image in the cover-image and a revealing network to reveal the secret image from the stego-image, both networks are made up of fully convolutional residual modules. The networks are jointly trained with a loss function which is the combination of chi-square distance (CSD) and mean-square error. The proposed MDRSteg are trained and tested on three datasets, Labeled Faces in the Wild, Pascal visual object classes, and ImageNet. Extensive experiments have been done and the experimental results suggest that the proposed model can not only hide a large size image in another image with good invisibility and large hiding capacity (24 bits-per-pixel), but also exhibits good generalization ability. The experimental results also show that dilated convolution, multi-scale fusion, and combined CSD loss function have positive effects on the delicate image steganography results and proves that the model is practically useful for many applications.
Long short-term memory improved Siamese network for robust target tracking

Abstract. Visual target tracking is an important function in real-time video monitoring application, whose performance determines the implementation of many advanced tasks. At present, Siamese-network trackers based on template matching show great potential. It has the advantage of balance between accuracy and speed, due to the pre-trained convolutional network to extract deep features for target representation and off-line tracking of each frame. During tracking, however, the target template feature is only obtained from the first frame of the video in the existing algorithms. The tracking performance is completely depending on the framework of template matching, resulting in the independence of frames and ignoring the feature of inter-frame connection of video sequence. Therefore, the existing algorithms do not perform well in the face of large deformation and severe occlusion. We propose a long short-term memory (LSTM) improved Siamese network (LSiam) model, which takes advantages of both time-domain regression capability of the LSTM and the balanced ability in tracking accuracy and speed of Siamese network. It focus on the temporal and spatial correlation information between video sequences to improve the traditional Siamese-network trackers with an LSTM prediction module. In addition, an improved template updating module is constructed to combine the original template with the changed appearance. The proposed model is verified in two types of difficult scenarios: deformation challenge and occlusion challenge. Experimental results show that our proposed approach can get better performance in terms of tracking accuracy.
Feature cross-fusion block net for accurate and efficient object detection

Abstract. In recent years, a number of detectors have been proposed to improve the accuracy and speed of object detection tasks. However, poor detection performances for small objects and difficulties in optimizing deep networks remain critical challenges for object detection. We try to tackle these problems in two ways. First, we propose an innovative cross-fusion block (CFB) module that can enhance the representational power of features for instances of small objects. In CFBs, high-level features with rich semantic information and low-level features from different layers at the same scale are cross-fused together. Second, we propose a periodic oscillation attenuation learning rate (POA_lr) that can effectively skip some purely locally optimal solutions in the training process to obtain better detection accuracy. Extensive experiments on PASCAL VOC and MS COCO datasets show that CFB and POA_lr can achieve higher detection accuracy while maintaining real-time processing speeds. The code will be made publicly available.
Static/dynamic filter with nonlocal regularizer

Abstract. Guided (joint) image filters play an important role in many computer vision and image processing applications. The main principle behind these filters is transferring the structural information from a guidance image to an input one. However, in practice, the structures between the two images are not always consistent. As a result, the filtering outputs become sensitive to outliers, which easily leads to texture-copying artifacts. Most recently, by relaxing the dependence on the guidance, static/dynamic (SD) filter overcomes the drawback effectively. With the SD strategy, this filter can jointly leverage structural information from the guidance and input. However, due to the locality of its regularizer, SD is prone to another deficiency, i.e., edge blurring. To tackle this problem, in our work, we extend SD filter to a nonlocal version [nonlocal static/dynamic (NSD)]. Particularly, a nonlocal regularizer is first established in a subspace transformed by partial least squares, which can better respect the unequal roles of the images. Then, to efficiently formulate the structural consistency between the two images (guidance and input), a novel joint term is plugged into the regularizer. Finally, an acceleration approach is designed to reduce the computational complexity induced by the nonlocal extension, which makes NSD achieve a comparable running time in practice. Thorough experimental results demonstrate that the proposed filter not only can avoid texture copy effectively but also can preserve edges powerfully.
The hydrodynamic genesis of linear karren patterns

Abstract In karst and alpine areas, the interactions between water and rocks give rise to a large variety of marvellous patterns. In this work, we provide a hydrodynamic model for the formation of dissolutional patterns made of parallel longitudinal channels, commonly referred to as linear karren forms. The model addresses a laminar film of water flowing on a rock that is dissolving. The results show that a transverse instability of the water–rock system leads to a longitudinal channelization responsible for the pattern formation. The instability arises because of a positive feedback within the channels between the higher water flow and the enhanced chemical dissolution. The spatial scales predicted by the linear stability analysis span different orders of magnitude depending on the Reynolds number. This may explain why similar patterns of different sizes are observed on natural rocks. Results also show that the rock solubility affects just the temporal scale of the instability and the rock inclination plays a minor role in the pattern formation. It is eventually discussed how rain is not strictly necessary for the appearance of linear karren patterns, but it may affect some of their features.
Incorporating tone in the modelling of wordlikeness judgements

Various phonotactic models have been proposed for the prediction of wordlikeness judgements, most of which have focused primarily on segments. This article aims to model wordlikeness judgements when tone is incorporated. We first show how the two major determinants of wordlikeness judgements, i.e. phonotactic probability and neighbourhood density, can be measured when tone is involved. To test the role of the two determinants of wordlikeness judgements in a tone language, judgement data were obtained from speakers of Cantonese. Bayesian modelling was then used to model the judgement data, showing that phonotactic probability, but not neighbourhood density, influences wordlikeness judgements. We also show that phonotactic probability affects the tendency to judge items as absolutely perfect or more or less wordlike, while it does not affect judgements that an item is absolutely not wordlike. Implications of these results for phonotactic modelling and processes involved in wordlikeness judgements are discussed.
Stern tube seals operation: A practical approach

Stern tube seals are a key component of the propulsion system of a ship. The purpose of these sealing rings is to ensure a reliable sealing condition, preventing the spillage of lubricant to the environment. The research on these large rotary seals is limited due to their complex accessibility: stern tube seals are located below the seawater level on a moving ship. A dynamic setup replicating the operating conditions of a stern tube seal is presented together with a novel arrangement for monitoring the flow rate across the seal. The frictional torque, the operating temperature, and the lubricant migration across the seal are measured under various shaft velocities and pressure differences. The existing theory for rotary lip seals is reviewed for the stern tube seal application. From the results it is deduced that the stern tube seals tested operate within the elastohydrodynamic regime with film thicknesses in the sub-micrometer range.
A low-delay information sharing algorithm for multiple-radio-per-platform networking

In order to ensure the strong real-time information sharing of Aerial Ad hoc Network, a low-delay information sharing algorithm for multiple-radio-per-platform networking is proposed based on the directional transmission capability of phased-array antenna. The algorithm introduces virtual nodes and virtual links in the process of topology generation first. By extracting topology information and choosing link grouping, it can effectively reduce redundant transmission and transmission latency of information sharing. Then, it is verified through simulation that the algorithm can reduce the latency by up to 49.8% and eliminate transmission redundancy. In addition, a direction selection algorithm is proposed for the variation of antenna beam direction. Simulation results show that the algorithm can further reduce the latency of information sharing and ensure the real time of information sharing, thus further improving the network performance.
Optimization of Microwave-Assisted Extraction of Phlorotannin From Sargassum swartzii (Turn.) C. Ag. With Ethanol/Water

Sargassum is a genus of brown macroalgae in the class Phaeophyta, distributed widely in all oceans, including those of Vietnam. Species of this genus have been proven to possess diverse biological activities, such as antioxidant, anti-fungal, and anti-inflammatory, along with many benefits and applications for human health, including anti-diabetic, obesity, and thrombosis. These benefits arise from a diverse chemical composition, with compounds such as fucoidan, mannitol, and especially phlorotannin—a group of phenolic derivatives found predominantly in brown algae. In this study, we evaluated and optimized the factors that affected the extraction process of phlorotannins from Sargassum swartzii (Turn.) C. Ag. , a common species of brown macroalgae in Vietnam. The process utilized ethanol and water as the solvent system, and the extraction process was assisted with the use of microwaves. To carry out optimization studies, Response Surface Methodology (RSM) was adopted according to a Central Composite Desisgn (CCD), taking four processing factors into consideration, ethanol concentration (%, v/v), extraction time (minutes), solvent/material ratio (v/w), and microwave output power (W) as independent variables. Phlorotannin concentration (mgPhE/g) and extract mass (mg) were regarded as optimization outcomes. Experimental conditions that produced the highest phlorotannin yield from 10 g of S. swartzii are as follows: Extraction time of 65 minutes, ethanol concentration of 52%, microwave output power of 613 W, and solvent/material ratio of 33/1 (v/w). These conditions corresponded to a phlorotannin concentration of 5.59 ± 0.11 mg PhE/g, and a total extract content of 27.88 ± 0.13 mg/g.
Activity of Cordycepin From Cordyceps sinensis Against Drug-Resistant Tumor Cells as Determined by Gene Expression and Drug Sensitivity Profiling

Cordycepin is one of the substantial components of the parasitic fungus Cordyceps sinensis as well as other Cordyceps species. It exerts various effects such as antimetastatic, antiinflammatory, antioxidant, and neuroprotective activities. Assorted studies revealed in vitro and in vivo anticancer influence of cordycepin and put forward its potential for cancer therapy. However, the role of multidrug resistance-associated mechanisms for the antitumor effect of cordycepin has not been investigated in great detail thus far. Therefore, we searched cordycepin’s cytotoxicity with regard to well-known anticancer drug resistance mechanisms, including ABCB1, ABCB5, ABCC1, ABCG2, EGFR, and TP53, and identified putative molecular determinants related to the cellular responsiveness of cordycepin. Bioinformatic analyses of NCI microarray data and gene promoter transcription factor binding motif analyses were performed to specify the mechanisms of cordycepin towards cancer cells. COMPARE and hierarchical analyses led to the detection of the genes involved in cordycepin’s cytotoxicity and sensitivity and resistance of cell lines towards cordycepin. Tumor-type dependent response and cross-resistance profiles were further unravelled. We found transcription factors potentially involved in the common transcriptional regulation of the genes identified by COMPARE analyses. Cordycepin bypassed resistance mediated by the expression of ATP-binding cassete (ABC) transporters (P-gp, ABCB5, ABCC1 and BCRP) and mutant epidermal growth factor receptor (EGFR). The drug sensitivity profiles of several DNA Topo I and II inhibitors were significantly correlated with those of cordycepin’s activity. Among eight different tumor types, prostate cancer was the most sensitive, whereas renal carcinoma was the most resistant to cordycepin. NF-κB was discovered as a common transcription factor. The potential of cordycepin is set forth as a potential new drug lead by bioinformatic evaluations. Further experimental studies are warranted for better understanding of cordycepin’s activity against cancer.
Modeling, comparison and evaluation of one-DOF six-bar bioinspired jumping leg mechanisms

One degree-of-freedom (DOF) jumping leg has the advantages of simple control and high stiffness, and it has been widely used in bioinspired jumping robots. Compared with four-bar jumping leg, six-bar jumping leg mechanism can make the robot achieve more abundant motion rules. However, the differences among different configurations have not been analyzed, and the choice of configurations lacks basis. In this study, five Watt-type six-bar jumping leg mechanisms were selected as research objects according to the different selection of equivalent tibia, femur and trunk link, and a method for determining the dimension of the jumping leg was proposed based on the movement law of jumping leg of locust in take-off phase. On this basis, kinematics indices (sensitivity of take-off direction angle and trunk attitude angle), dynamics indices (velocity loss, acceleration fluctuation, and mean and variance of total inertial moment) and structure index (distribution of center of mass) were established, and the differences of different configurations were compared and analyzed in detail. Finally, according to the principal component analysis method, the optimal selection method for different configurations was proposed. This study provides a reference for the design of one DOF bioinspired mechanism.
Semi-active control of a nonlinear quarter-car model of hyperloop capsule vehicle with Skyhook and Mixed Skyhook-Acceleration Driven Damper controller

A suspension system is one of the integral parts of a hyperloop capsule train, which is used to isolate the car-body from bogie vibration to provide a safer and comfortable service. A semi-active suspension system is one of the best candidates for its advantageous features. The performance of a semi-active suspension system relies greatly on the control strategy applied. In this article, Skyhook (SH) and mixed Skyhook-Acceleration Driven Damper (SH-ADD) controlling algorithms are adopted for a nonlinear quarter-car model of a capsule with semi-active magnetorheological damper. The nonlinear vertical dynamic response and performance of the proposed control algorithms are evaluated under MATLAB Simulink environment and hardware-in-loop-system (HILS) environment. The SH controlled semi-active suspension system performance is found to be better at the first resonance frequency and worse at the second resonance frequency than the passive MR damper, but the mixed SH-ADD controlled semi-active suspension system performs better than the passive at all frequency domains. Taking the root-mean-square (RMS) value of sprung mass vertical displacement as an evaluation criterion, the response is reduced by 58.49% with mixed SH-ADD controller and by 54.49% with the SH controller compared to the passive MR damper suspension.
Polycation-Grafted Poly(vinylidene fluoride) Membrane with Biofouling Resistance

Covalent immobilization of polycations onto a membrane surface has been shown to significantly improve the resistance to biofouling. The poly(vinylidene fluoride)-graft-poly(N,N-dimethylamino-2-ethylmethacrylate) (PVDF-g-PDMAEMA) copolymer was synthesized via radical grafting copolymerization and fabricated into a flat membrane. The polycation membrane surface was constructed by quaternization of PDMAEMA side chains with 1,5-dibromopentane and diquaternization of 4,4′-bipyridine. As revealed by membrane surface morphology, pore size, and porosity measurement, the polycations are distributed on the membrane surface and internal pore channel surface. Water contact angles confirm that the incorporation of polycations remarkably promotes the surface hydrophilicity of a membrane. The polycation membrane surface provides an excellent bactericidal efficiency against Escherichia coli.
Enrichment of novel Verrucomicrobia, Bacteroidetes, and Krumholzibacteria in an oxygen‐limited methane‐ and iron‐fed bioreactor inoculated with Bothnian Sea sediments

Microbial methane oxidation is a major biofilter preventing larger emissions of this powerful greenhouse gas from marine coastal areas into the atmosphere. In these zones, various electron acceptors such as sulfate, metal oxides, nitrate, or oxygen can be used. However, the key microbial players and mechanisms of methane oxidation are poorly understood. In this study, we inoculated a bioreactor with methane‐ and iron‐rich sediments from the Bothnian Sea to investigate microbial methane and iron cycling under low oxygen concentrations. Using metagenomics, we investigated shifts in microbial community composition after approximately 2.5 years of bioreactor operation. Marker genes for methane and iron cycling, as well as respiratory and fermentative metabolism, were identified and used to infer putative microbial metabolism. Metagenome‐assembled genomes representing novel Verrucomicrobia, Bacteroidetes, and Krumholzibacteria were recovered and revealed a potential for methane oxidation, organic matter degradation, and iron cycling, respectively. This work brings new hypotheses on the identity and metabolic versatility of microorganisms that may be members of such functional guilds in coastal marine sediments and highlights that microorganisms potentially composing the methane biofilter in these sediments may be more diverse than previously appreciated.
Editorial: The Privatization of Work-Related Risk Control

Abstract This introduction starts by linking the privatization of work-related risk control to a political context in which social investment policies are prominent. Subsequently, a short overview of different forms of privatization is given. Finally, the different contributions to this special issue are introduced by either relating them to the governance or the consequences of privatization. Based on the contributions to the special issue, it is concluded first that the governance of privatized risk control poses difficult challenges of finding the right balance between public objectives and the involvement of private interests. Secondly, it is concluded that, by excluding or marginalizing the most vulnerable group, the privatization of risk control does not always achieve the equality of opportunities that social investment policies aim for. These risks of exclusion and marginalization seem to be particularly salient when the privatization of social investment policies is embedded in a context of retrenchment or a dualization of the labor market.
Domestication effects on aggressiveness: Comparison of biting motivation and bite force between wild and domesticated finches

Domesticated animals evolve unique traits, known as domestication phenotypes or the domestication syndrome, due to their adaptation to a captive environment and changes in selection pressures. After being tamed, the Bengalese finch (Lonchura striata var. domestica) has undergone behavioural and physiological trait changes that differ from those of its wild ancestor, the white-rumped munia (Lonchura striata). The Bengalese finch has complex songs, lower fear response, and lower corticosterone levels than those in the white-rumped munia. We hypothesized that domesticated finches increase the effort to reproduce in lieu of maintaining fitness for survival as needed in the wild. Aggressiveness and bite performance affect survival rates and reproductive success, and are good indicators of adaptability in the natural environment. Therefore, we compared the aggressiveness and biting force of white-rumped munias with those of Bengalese finches to explore the evolutionary mechanisms of behavioural changes due to domestication. We found that the Bengalese finch had decreased aggressiveness (incidence of aggressive biting birds and the number of bite responses) and bite force than those in the white-rumped munia due to domestication. Therefore, we believe they could allocate more resources for breeding that would otherwise be needed for coping with predators through aggression.
Effects of L-Dopa, SKF-38393, and quinpirole on exploratory, anxiety- and depressive-like behaviors in pubertal female and male mice

Adolescence is a phase of substantial changes in the brain, characterized by maturational remodeling of many systems. This remodeling allows functional plasticity to adapt in a changing environment but turns this period into a neurodevelopmental vulnerable window. The dopaminergic system is under morphological and physiological changes during this phase. The disruption of its balance can lead to molecular variation and abnormal behavior - representing a risk factor for neuropsychiatric disorders. In the present study, we investigated if changes in the dopaminergic tone alter mice behavior in a receptor and sex-specific manner, specifically in the beginning of puberty period. We administered L-Dopa, SKF-38393 (D1 dopamine receptor agonist) and Quinpirole (D2 dopamine receptor agonist) and tested male and female mice motor, anxiety- and depressive-like behavior. While females displayed an impaired exploratory drive, males presented an intense depressive-like response. Our results provide insights into the function of dopaminergic development in adolescent behavior and highlight the importance of studies in this time window with male and female subjects.