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Diabetic nephropathy (DN) is the predominant secondary nephropathy resulting in global end‐stage renal disease. It is attracting significant attention in both domestic and international research due to its widespread occurrence, fast advancement, and limited choices for prevention and treatment. The pathophysiology of this condition is intricate and involves multiple molecular and cellular pathways at various levels. This article provides a concise overview of the molecular processes involved in the development of DN. It discusses various factors, such as signaling pathways, cytokines, inflammatory responses, oxidative stress, cellular damage, autophagy, and epigenetics. The aim is to offer clinicians a valuable reference for DN's diagnosis, treatment, and intervention. [ABSTRACT FROM AUTHOR]

Image data augmentation plays a crucial role in data augmentation (DA) by increasing the quantity and diversity of labeled training data. However, existing methods have limitations. Notably, techniques like image manipulation, erasing, and mixing can distort images, compromising data quality. Accurate representation of objects without confusion is a challenge in methods like auto augment and feature augmentation. Preserving fine details and spatial relationships also proves difficult in certain techniques, as seen in deep generative models. To address these limitations, we propose OFIDA, an object-focused image data augmentation algorithm. OFIDA implements one-to-many enhancements that not only preserve essential target regions but also elevate the authenticity of simulating real-world settings and data distributions. Specifically, OFIDA utilizes a graph-based structure and object detection to streamline augmentation. Specifically, by leveraging graph properties like connectivity and hierarchy, it captures object essence and context for improved comprehension in real-world scenarios. Then, we introduce DynamicFocusNet, a novel object detection algorithm built on the graph framework. DynamicFocusNet merges dynamic graph convolutions and attention mechanisms to flexibly adjust receptive fields. Finally, the detected target images are extracted to facilitate one-to-many data augmentation. Experimental results validate the superiority of our OFIDA method over state-of-the-art methods across six benchmark datasets. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to explore the contribution of differentially expressed programmed cell death genes (DEPCDGs) to the heterogeneity of serous ovarian cancer (SOC) through single-cell RNA sequencing (scRNA-seq) and assess their potential as predictors for clinical prognosis. Methods: SOC scRNA-seq data were extracted from the Gene Expression Omnibus database, and the principal component analysis was used for cell clustering. Bulk RNA-seq data were employed to analyze SOC-associated immune cell subsets key genes. CIBERSORT and single-sample gene set enrichment analysis (ssGSEA) were utilized to calculate immune cell scores. Prognostic models and nomograms were developed through univariate and multivariate Cox analyses. Results: Our analysis revealed that 48 DEPCDGs are significantly correlated with apoptotic signaling and oxidative stress pathways and identified seven key DEPCDGs (CASP3, GADD45B, GNA15, GZMB, IL1B, ISG20, and RHOB) through survival analysis. Furthermore, eight distinct cell subtypes were characterized using scRNA-seq. It was found that G protein subunit alpha 15 (GNA15) exhibited low expression across these subtypes and a strong association with immune cells. Based on the DEGs identified by the GNA15 high- and low-expression groups, a prognostic model comprising eight genes with significant prognostic value was constructed, effectively predicting patient overall survival. Additionally, a nomogram incorporating the RS signature, age, grade, and stage was developed and validated using two large SOC datasets. Conclusion: GNA15 emerged as an independent and excellent prognostic marker for SOC patients. This study provides valuable insights into the prognostic potential of DEPCDGs in SOC, presenting new avenues for personalized treatment strategies. [ABSTRACT FROM AUTHOR]

• A restoration flexibility quantification method is developed for EB clusters. • A two-step collaborative restoration strategy for the resilient DS is proposed. • Uncertainties associated with the EB cluster dispatch time and renewables power outputs are well addressed by using rolling optimization method. The widespread deployment of electric buses (EBs) offers substantial flexibility resources to support the service restoration and enhance the resilience of distribution system (DS). Therefore, this paper presents a comprehensive and collaborative service restoration strategy for resilient DS, considering the support of EBs. First, the restoration flexibility model for EBs is derived, which quantifies the restoration capability of EBs by dividing effective EB clusters. This model is integrated into the DS restoration process. Then, a two-step collaborative restoration method of DS is proposed with the aim of minimizing the load curtailment cost. The first step addresses the restoration planning problem to determine the dispatch decisions for EB clusters. Based on above planning solutions, the second step focuses on the real-time restoration problem of DS, obtaining optimal restoration results through coordinating EB clusters and other local resources. In this stage, the impact of natural disasters on the EB cluster dispatch in transportation system is considered, and a rolling optimization method is employed to deal with uncertainties from renewables, load, and EB cluster dispatch time. Finally, numerical simulations are conducted using the modified IEEE 33-bus distribution test system and a 29-node transportation system to verify the effectiveness of the proposed restoration method. [ABSTRACT FROM AUTHOR]

In a recent study, it was shown that, with adversarial training of an attentive generative network, it is possible to convert a raindrop degraded image into a relatively clean one. However, in real world, raindrop appearance is not only formed by individual raindrops, but also by the distant raindrops accumulation and the atmospheric veiling, namely haze. Current methods are limited in extracting accurate features from a raindrop degraded image with background scene, the blurred raindrop regions, and the haze. In this paper, we propose a new model for an image corrupted by the raindrops and the haze, and introduce an integrated multi-task algorithm to address the joint raindrop and haze removal (JRHR) problem by combining an improved estimate of the atmospheric light, a modified transmission map, a generative adversarial network (GAN) and an optimized visual attention network. The proposed algorithm can extract more accurate features for both sky and non-sky regions. Experimental evaluation has been conducted to show that the proposed algorithm significantly outperforms state-of-the-art algorithms on both synthetic and real-world images in terms of both qualitative and quantitative measures. [ABSTRACT FROM AUTHOR]

In this paper, we consider the problem of recovering the phase information of the multiple images from the multiple mixed phaseless short-time Fourier transform image measurements, which is called the blind multiple-input multiple-output image phase retrieval (BMIPR) problem. It is an inherently ill-posed problem due to the lack of the phase and mixing information, and the existing phase retrieval algorithms are not explicitly designed for this case. To address the BMIPR phase retrieval problem, an integrated algorithm is presented, which combines a gradient descent algorithm by minimizing a nonconvex loss function with an independent component analysis algorithm and a nonlocal means algorithm. Experimental evaluation has been conducted to show that under appropriate conditions, the proposed algorithms can explicitly recover the images, the phases of the images, and the mixing matrix. In addition, the algorithm is robust to noise. [ABSTRACT FROM AUTHOR]

In this paper, we consider the problem of recovering the phase information of multiple sources from a mixed phaseless short-time Fourier transform measurement, which is called multiple input single output (MISO) phase retrieval problem. It is an inherently ill-posed problem due to the lack of the phase and mixing information, and the existing phase retrieval algorithms are not explicitly designed for this case. To address the MISO phase retrieval problem, a least-squares method coupled with an independent component analysis (ICA) algorithm is proposed for the case of sufficiently long window length. When these conditions are not met, an integrated algorithm is presented, which combines a gradient descent algorithm by minimizing a non-convex loss function with an ICA algorithm. Experimental evaluation has been conducted to show that under appropriate conditions the proposed algorithms can explicitly recover the signals, the phases of the signals, and the mixing matrix. In addition, the algorithm is robust to noise. [ABSTRACT FROM AUTHOR]

In a recent study of auditory evoked potential (AEP) based brain–computer interface (BCI), it was shown that, with an encoder–decoder framework, it is possible to translate human neural activity to speech (T-CAS). Current encoder–decoder-based methods achieve T-CAS often with a two-step approach where the information is passed between the encoder and decoder with a shared vector of reduced dimension, which, however, may result in information loss. In this paper, we propose an end-to-end model to translate human neural activity to speech (ET-CAS) by introducing a dual–dual generative adversarial network (Dual-DualGAN) for cross-domain mapping between electroencephalogram (EEG) and speech signals. In this model, we bridge the EEG and speech signals by introducing transition signals which are obtained by cascading the corresponding EEG and speech signals in a certain proportion. We then learn the mappings between the speech/EEG signals and the transition signals. We also develop a new EEG dataset where the attention of the participants is detected before the EEG signals are recorded to ensure that the participants have good attention in listening to speech utterances. The proposed method can translate word-length and sentence-length sequences of neural activity to speech. Experimental results show that the proposed method significantly outperforms state-of-the-art methods on both words and sentences of auditory stimulus. [ABSTRACT FROM AUTHOR]

In a recent study, it was shown that, given only the magnitude of the short-time Fourier transform (STFT) of a signal, it is possible to recover the phase information of its STFT under certain conditions. However, this is only investigated for the single-source scenario. In this paper, we extend this work and formulate a multi-source phase retrieval problem where multi-channel phaseless STFT measurements are given as input. We then present a robust multi-source phase retrieval (RMSPR) algorithm based on a gradient descent (GD) algorithm by minimizing a non-convex loss function and independent component analysis (ICA). An improved least squares (LS) loss function is presented to find the initialization of the GD algorithm. Experimental evaluation has been conducted to show that under appropriate conditions the proposed algorithm can explicitly recover the phase of the sources, the mixing matrix, and the sources simultaneously, from noisy measurements. [ABSTRACT FROM AUTHOR]

The variation of microstructure and microtexture across a Ti-6Al-4V (Ti64) linear friction weld was investigated using scanning electron microscopy (SEM) and electron backscattered diffraction (EBSD). Pole figures and misorientations distribution obtained from α phase show four distinct regions within the weld, with different textural characteristics. Nevertheless, the main texture components remain the same in centre weld zone and thermal mechanical affected zone with the basal poles of the α phases located at around 0°, 60° and 90° to the sample normal (Z 0 ) direction. The results indicate that the texture components are strongly related to the amount of transformed β phase. The deformation of the primary α grains has a limited effect on the texture development. [ABSTRACT FROM AUTHOR]

We report the formation of NiGe nanowires by the thermal decomposition of diphenylgermane, in the presence of a bulk Ni foil, in a solvent vapor growth system. The reaction occurs by the initial formation of a NiGe layer on the foil which progresses to the growth of nanowire occlusions of the same phase, typically 40 nm in diameter. Switching the substrate from bulk Ni foil to an evaporated layer of Ni results in the growth of NiGe seeded germanium nanowires, in high yield. The nanowires were characterized using high resolution scanning electron microscopy, X-ray diffraction, and high resolution transmission electron microscopy. [ABSTRACT FROM AUTHOR]

The main objective of this work was to investigate the thermomechanical behavior and microstructural changes of a Ti-rich NiTi shape memory alloy (SMA). The microstructural and texture evolution of aged NiTi alloy at different degrees of deformation were elicited by transmission electron microscopy (TEM). An effort was made to correlate results obtained from the tensile test with results from microstructure studies. The undeformed sample reveals a self-accommodated morphology with straight and well defined twin boundaries. At different stages of deformation, diverse mechanisms were involved. These mechanisms include marstraining, detwinning accompanied by dislocation movement, and finally, severe plastic deformation, subdivision and amorphization of the matrix. Under increasing strains, high density lattice defects were generated and the morphology of B19’ became disordered. [ABSTRACT FROM AUTHOR]

5 wt.% yttria doped mullite ceramics were sintered using nanocomposite powders which consisted of a Y 2 O 3 –SiO 2 core coated with pseudoboehmite. Firstly, the powders were heated up to 1300 °C; mullite began to form at 1050 °C which is ∼150 °C lower than in previous diphasic precursors. Then, the powders were sintered at 1550 °C for 0.5, 5 and 48 h, and characterized using XRD, SEM and TEM with EDS. The phases present were mullite and two intergranular glasses comprising silica-rich droplets embedded in a Y–Si–Al–O glassy matrix, providing direct evidence of liquid-liquid phase separation at the grain boundaries during sintering. This liquid-liquid separation is facilitated by the prior existence of yttrium disilicate which moves the overall sintering liquid compositions toward the two immiscible liquids region of the Y 2 O 3 –Al 2 O 3 –SiO 2 phase diagram. The presence of the silica-rich phase in the grain boundaries will effectively increase their viscosity and thus the resistance of the Y 2 O 3 densified mullite to creep. [ABSTRACT FROM AUTHOR]

Surface Electromyography (sEMG) is widely used in evaluating the functional status of hands to assist in hand gesture recognition in many fields of treatment and rehabilitation. Multi-channel parallel interfaces (MCPIs) or time-division multiple access (TDMA) interfaces are the main technologies for the man–machine communication medium of sEMG recognition instruments. However, they can also result in a complex circuit connection and noise interference. A hand gesture recognition model based on sEMG signals by using single-mixture source separation and flexible neural trees (FNTs) is a breakthrough model of hand gesture recognition designed to conquer the above defects. It distinguishes itself from the traditional MCPI or TDMA interfaces by more accurate and reliable measurements of signals. Single-mixture source separation by use of ensemble empirical mode decomposition (EEMD), principal component analysis (PCA) and independent component analysis (ICA) is a novel single-input multiple-output (SIMO) blind separation method, which can simplify the two interfaces described above. The FNT model is generated and evolved based on the pre-defined simple instruction sets, which can solve the highly structure dependent problem of the artificial neural network. The testing has been conducted using several experiments conducted with five participants. The EEMD-PCA-ICA algorithm can blind separate single mixed signals with higher cross-correlation and lower relative root mean squared error. The results indicate that the model is able to classify four different hand gestures up to 97.48% accuracy. [ABSTRACT FROM PUBLISHER]

Recent experimental work in lung morphogenesis has described an elegant pattern of branching phenomena. Two primary forms of branching have been identified: side branching and tip splitting. In our previous study of lung branching morphogenesis, we used a 4 variable partial differential equation (PDE), due to Meinhardt, as our mathematical model to describe the reaction and diffusion of morphogens creating those branched patterns. By altering key parameters in the model, we were able to reproduce all the branching styles and the switch between branching modes. Here, we attempt to explain the branching phenomena described above, as growing out of two fundamental instabilities, one in the longitudinal (growth) direction and the other in the transverse direction. We begin by decoupling the original branching process into two semi-independent sub-processes, 1) a classic activator/inhibitor system along the growing stalk, and 2) the spatial growth of the stalk. We then reduced the full branching model into an activator/inhibitor model that embeds growth of the stalk as a controllable parameter, to explore the mechanisms that determine different branching patterns. We found that, in this model, 1) side branching results from a pattern-formation instability of the activator/inhibitor subsystem in the longitudinal direction. This instability is far from equilibrium, requiring a large inhomogeneity in the initial conditions. It successively creates periodic activator peaks along the growing stalk, each of which later on migrates out and forms a side branch; 2) tip splitting is due to a Turing-style instability along the transversal direction, that creates the spatial splitting of the activator peak into 2 simultaneously-formed peaks at the growing tip, the occurrence of which requires the widening of the growing stalk. Tip splitting is abolished when transversal stalk widening is prevented; 3) when both instabilities are satisfied, tip bifurcation occurs together with side branching. [ABSTRACT FROM AUTHOR]

Recent experimental work has described an elegant pattern of branching in the development of the lung. Multiple forms of branching have been identified, including side branching and tip bifurcation. A particularly interesting feature is the phenomenon of 'orthogonal rotation of the branching plane'. The lung must fill 3D space with the essentially 2D phenomenon of branching. It accomplishes this by rotating the branching plane by 90° with each generation. The mechanisms underlying this rotation are not understood. In general, the programmes that underlie branching have been hypothetically attributed to genetic 'subroutines' under the control of a 'global master routine' to invoke particular subroutines at the proper time and location, but the mechanisms of these routines are not known. Here, we demonstrate that fundamental mechanisms, the reaction and diffusion of biochemical morphogens, can create these patterns. We used a partial differential equation model that postulates three morphogens, which we identify with specific molecules in lung development. We found that cascades of branching events, including side branching, tip splitting and orthogonal rotation of the branching plane, all emerge immediately from the model, without further assumptions. In addition, we found that one branching mode can be easily switched to another, by increasing or decreasing the values of key parameters. This shows how a 'global master routine' could work by the alteration of a single parameter. Being able to simulate cascades of branching events is necessary to understand the critical features of branching, such as orthogonal rotation of the branching plane between successive generations, and branching mode switch during lung development. Thus, our model provides a paradigm for how genes could possibly act to produce these spatial structures. Our low-dimensional model gives a qualitative understanding of how generic physiological mechanisms can produce branching phenomena, and how the system can switch from one branching pattern to another using low-dimensional 'control knobs'. The model provides a number of testable predictions, some of which have already been observed (though not explained) in experimental work. [ABSTRACT FROM AUTHOR]

Blind source separation (BSS) of single-channel mixed recording is a challenging task that has applications in the fields of speech, audio and bio-signal processing. Ensemble empirical mode decomposition (EEMD)-based methods are commonly used for blind separation of single input multiple outputs. However, all of these EEMD-based methods appear in the edge effect problem when cubic spline interpolation is used to fit the upper and lower envelopes of the given signals. It is therefore imperative to have good methods to explore a more suitable design choice, which can avoid the problems mentioned above as much as possible. In this paper we present a novel single-mixture blind source separation method based on edge effect elimination of EEMD, principal component analysis (PCA) and independent component analysis (ICA). EEMD represents any time-domain signal as the sum of a finite set of oscillatory components called intrinsic mode functions (IMFs). In extreme point symmetry extension (EPSE), optimum values of endpoints are obtained by minimizing the deviation evaluation function of signal and signal envelope. Edge effect is turned away from signal by abandoning both ends' extension parts of IMFs. PCA is applied to reduce dimensions of IMFs. ICA finds the independent components by maximizing the statistical independence of the dimensionality reduction of IMFs. The separated performance of edge EPSE-EEMD-PCA-ICA algorithm is compared with EEMD-ICA and EEMD-PCA-ICA algorithms through simulations, and experimental results show that the former algorithm outperforms the two latter algorithms with higher correlation coefficient and lower relative root mean square error (RRMSE). [ABSTRACT FROM AUTHOR]

Abstract: The microhardness and microstructure of linear friction welded Ti–6Al–2Sn–4Zr–6Mo (Ti6246) alloys were studied, in both as-welded and post-weld heat-treated conditions. It has been found that the as-welded Ti6246 has a lower microhardness value of about 360HV in the central weld zone than that of the base material of about 420HV. Post-weld heat-treatment of the Ti6246 weld at 600°C for 1h has led to the hardness increase of about 180HV at the central weld zone. Transmission electron microscopy studies show that the microstructure at the central weld zone of the as-welded Ti6246 consists of fine grains with dense acicular orthorhombic α″ martensite. The soft α″ martensite is believed to account for the low hardness measured in the as-welded conditions. Phase transformation from orthorhombic α″ to hexagonal α occurred during the PWHT, resulting in the observed hardness increase. [Copyright &y& Elsevier]

Blind source separation of single-channel mixed recording is a challenging task that has applications in the fields of speech, audio and bio-signal processing. Numerous blind source separation methods are commonly used for blind separation of single input multiple output. However, the priori knowledge of the signal is assumed to be known or the main channels selected from multi-channel output are not self-adaptive and automatic. Presented in this paper is a new method based on dimensionality reduction of ensemble empirical mode decomposition (EEMD), and ICA does not rely on such assumptions. The EEMD represents any time-domain signal as the sum of a finite set of oscillatory components called intrinsic mode functions (IMFs). ICA finds the independent components by maximizing the statistical independence of the dimensionality reduction IMFs. Principal component analysis (PCA) is applied to reduce dimensions of IMFs. The separated performance of EEMD-PCA-ICA algorithm is compared with EEMD-ICA through simulations, and experimental results show EEMD-PCA-ICA algorithm outperforms EEMD-ICA with higher cross-correlation and lower relative root mean squared error (RRMSE). [ABSTRACT FROM AUTHOR]

A chromium-free composite conversion treatment for magnesium by phytic acid and CeCl solutions was studied. The composite coatings on the surface of magnesium presented network-like cracks, which was consisted of Mg, O, C, P and Ce elements. The distribution of Ce on the surface layer was non-uniform. The crack sizes of the composite coating were smaller than that of the phytic acid conversion coating. The corrosion process of the coatings was evaluated through electrochemical impedance spectroscopy in 3.5% NaCl solution, and the equivalent circuit of RL(Q(R(QR))) model was obtained through the characteristics of EIS. The average corrosion rate of the composite coating was reduced at least 50% compared with that of pure phytic acid conversion coating. [ABSTRACT FROM AUTHOR]

To determine if job stress, health, and presenteeism differ between healthcare workers at Chinese public and private hospitals. This cross-sectional study analyzed the records of 1080 healthcare workers in eastern, central, and western China for the period from January2015 through November2015. Data on challenge stress, hindrance stress, health, and presenteeism were collected. Using univariate and multivariate regression and SPSS, we investigated differences between Chinese public and private hospitals in China. Challenge stress, hindrance stress, and presenteeism, but not health status, significantly differed between healthcare workers at public and private hospitals in China. Challenge stress and hindrance stress were significantly higher in public hospitals, while presenteeism was significantly lower in private hospitals. The significant differences between public and private hospitals are attributable to differences in the business practices and management of public and private hospitals. To achieve successful long-term medical reform in China, the adverse effects of psychosocial factors should be considered in future research plans and policies. Chinese hospitals urgently require improvements in management and leadership. Reform efforts should encompass fields such as management science, psychology, and the behavioral sciences. [ABSTRACT FROM AUTHOR]

Owing to the increasing market demand of Codonopsis Radix, the cropper blindly cultivates to expand planting area for economic benefits, which seriously affects the quality of Codonopsis Radix. Therefore, this study synthesized 207 batches of Codonopsis Radix and 115 ecological factors, and analyzed the suitable planting areas of Codonopsis pilosula under current and future climate change based on Geographic Information System (GIS) and MaxEnt model. Secondly, we evaluated the quality of Codonopsis Radix based on the all-in-one functional factor including chromatographic fingerprint, the index components, the effective compounds groups, the nutritional components, and the nutritional elements, and the quality regionalization of Codonopsis Radix was analyzed. Finally, the ecological factors affecting the accumulation of effective components of Codonopsis Radix were analyzed. This study found for the first time that the highly suitable area of Codonopsis pilosula was mainly distributed in the Weihe River system and the Bailongjiang River system in Gansu Province. There were differences in the quality of Codonopsis Radix from different ecologically suitable areas based on the all-in-one functional factors, and the comprehensive high-quality area of Codonopsis Radix was mainly distributed in Longnan and Longxi district of Gansu Province. The precipitation, temperature and altitude play a key role in the accumulation of chemical components in the 10 ecological factors affecting the distribution of Codonopsis pilosula. Under future climatic conditions, the highly suitable area of Codonopsis pilosula is decreased. [ABSTRACT FROM AUTHOR]

We developed and validated a multimodal radiomic machine learning approach to noninvasively predict the expression of lymphocyte cell-specific protein-tyrosine kinase (LCK) expression and clinical prognosis of patients with high-grade serous ovarian cancer (HGSOC). We analyzed gene enrichment using 343 HGSOC cases extracted from The Cancer Genome Atlas. The corresponding biomedical computed tomography images accessed from The Cancer Imaging Archive were used to construct the radiomic signature (Radscore). A radiomic nomogram was built by combining the Radscore and clinical and genetic information based on multimodal analysis. We compared the model performances and clinical practicability via area under the curve (AUC), Kaplan–Meier survival, and decision curve analyses. LCK mRNA expression was associated with the prognosis of HGSOC patients, serving as a significant prognostic marker of the immune response and immune cells infiltration. Six radiomic characteristics were chosen to predict the expression of LCK and overall survival (OS) in HGSOC patients. The logistic regression (LR) radiomic model exhibited slightly better predictive abilities than the support vector machine model, as assessed by comparing combined results. The performance of the LR radiomic model for predicting the level of LCK expression with five-fold cross-validation achieved AUCs of 0.879 and 0.834, respectively, in the training and validation sets. Decision curve analysis at 60 months demonstrated the high clinical utility of our model within thresholds of 0.25 and 0.7. The radiomic nomograms were robust and displayed effective calibration. Abnormally high expression of LCK in HGSOC patients is significantly correlated with the tumor immune microenvironment and can be used as an essential indicator for predicting the prognosis of HGSOC. The multimodal radiomic machine learning approach can capture the heterogeneity of HGSOC, noninvasively predict the expression of LCK, and replace LCK for predictive analysis, providing a new idea for predicting the clinical prognosis of HGSOC and formulating a personalized treatment plan. [ABSTRACT FROM AUTHOR]

Location-based services (LBS) are widely used due to the rapid development of mobile devices and location technology. Users usually provide precise location information to LBS to access the corresponding services. However, this convenience comes with the risk of location privacy disclosure, which can infringe upon personal privacy and security. In this paper, a location privacy protection method based on differential privacy is proposed, which efficiently protects users' locations, without degrading the performance of LBS. First, a location-clustering (L-clustering) algorithm is proposed to divide the continuous locations into different clusters based on the distance and density relationships among multiple groups. Then, a differential privacy-based location privacy protection algorithm (DPLPA) is proposed to protect users' location privacy, where Laplace noise is added to the resident points and centroids within the cluster. The experimental results show that the DPLPA achieves a high level of data utility, with minimal time consumption, while effectively protecting the privacy of location information. [ABSTRACT FROM AUTHOR]

Doping of a 2.5 wt.% Au/Al 2 O 3 catalyst with potassium ions (3 wt.%) leads to a significantly increased rate by > 1 order of magnitude of decomposition of formic acid at 358 K as compared to an undoped catalyst with the same mean Au particle size (2.6 nm). The doped catalyst gave stable and CO-free (< 10 ppm CO) hydrogen production. The mechanism of the reaction changed. This was provided by a significantly increased content of a reaction intermediate – formate ions (HCOO − ) controlled by K + counterions in formic acid condensed in the pores of the catalyst. [ABSTRACT FROM AUTHOR]

Recently, we confirmed that the 95% ethanol‐extracted fraction of Codonopsis Radix, which contains several triterpenoids and sterols, possesses pharmacological activities. However, due to the low content and diverse types of triterpenoids and sterols, their similar structures, lack of ultraviolet absorption, and difficulty in obtaining controls, few studies have so far assessed their contents in Codonopsis Radix. We accordingly constructed an ultra‐high‐performance liquid chromatography‐quadrupole‐time‐of‐flight mass spectrometry technique for the simultaneous quantitative determination of 14 terpenoids and sterols. Separation was performed on the Waters Acquity UPLC HSS T3 C18 column (100 × 2.1 mm, 1.8 μm) with 0.1% formic acid (A) and 0.1% formic acid in methanol (B) as mobile phase under gradient elution. The determination coefficients for each of the matrix calibration curves were ≥0.9925. The average recovery ranged from 81.25% to 118.05%, with relative standard deviations of <4%. The contents of 14 components in 23 batches were quantified and further analyzed through chemometrics. Linear discriminant analysis can distinguish sample varieties. The quantitative analysis method can accurately determine the contents of 14 components and thereby provide the chemical basis for the quality control of Codonopsis Radix. It also could be a valuable approach for the classification of different Codonopsis Radix varieties. [ABSTRACT FROM AUTHOR]

Existing electroencephalogram (EEG) collection devices primarily include EEG collection systems for medical scientific research and BrainLink or earphones for commercial advertising. The EEG collection systems employ multiple-input multiple-output connections, making the circuit and wiring complex. However, the BrainLink or earphones are usually designed for entertainment mainly collecting one or two EEG locations. To address these problems, in this paper, a multiple-input single-output collection device (MISOCD) is developed that can obtain a single-channel mixed signal, and a multiple-input single-output blind separation (MISOBS) algorithm is proposed to separate multiple-channel signals from a single-channel mixed signal by introducing an improved parallel dual generative adversarial network that can build one-to-multiple mapping. An experiment is conducted on synthetic signals to illustrate the separation performance of the proposed MISOBS algorithm, which significantly outperforms the state-of-the-art algorithms. The real signals collected by the MISOCD are used for gesture recognition. [ABSTRACT FROM AUTHOR]

Fe2O3–Ag hollow microspheres (FAHMs) with crumpled surfaces were prepared by solvothermal treatment with post-calcination. The as-prepared hybrid microspheres were first used as an active substrate for surface-enhanced Raman scattering (SERS) of a small molecule, 4-aminobenzenethiol (4-ABT), and an enhancement factor of 9.6 × 104 was achieved. In addition, the FAHMs provided photocatalytic activity to the absorbed 4-ABT after exposure to visible light for 5 min and can be recycled five times without a decrease in the SERS performance. Furthermore, the prepared FAHMs are also a possible substrate for macromolecule ricin and the recyclability can be achieved by water activation. [ABSTRACT FROM AUTHOR]

An investigation was carried out into the influence of the annealing temperatures on the thermo-mechanical behavior of Ti-rich NiTi alloy with regard to transformation temperatures, mechanical properties at room temperature and microstructure evolution under deformation. It was found that annealing above the recrystallization temperature (600 °C) modulated the mechanical behavior of the alloy significantly. Based on tensile and DSC analysis, it was observed that by increasing the annealing temperature, the shape memory behavior of the alloys improved. Scanning and transmission electron microscopy were used to investigate the fracture surfaces and microstructural evolution of the NiTi samples after failure. Fractography revealed the brittle fracture area produced through the propagation of cleavage cracks; however, ductile fracture via nucleation growth and coalescence of micro-dimples in the martensitic phase at room temperature were also observed. During plastic deformation, the NiTi alloy was also observed to undergo a detwinning process, dislocation slip and the formation of submicrocrystalline grains, nanocrystallization and amorphous bands. [ABSTRACT FROM AUTHOR]

Martensitic evolution in Ti-rich NiTi alloy, Ti50.5Ni49.5, has been investigated as a function of annealing, solution treatment and a combination thereof and a detailed electron microscopic investigation carried out. Self-accommodated martensite plates resulted in all heat treated samples. Martensitic < 011 > type II twins, which are common in NiTi shape memory alloys, was found in both as-received and heat-treated samples. Solution treated samples, additionally, showed {11-1} type I twinning was also found in samples that have been annealed after solution-treatment. Another common feature of the microstructure in both as-received and heat treated samples is the formation of Ti 2 Ni precipitates. The size, number and dispersions of these precipitates can be controlled by resorting to a suitable heat treatment e.g. solution treatment. [ABSTRACT FROM AUTHOR]

In real world, images always do not have the ground truth that we can compare with. Therefore, we consider blind image quality assessment (BIQA) no-reference methods for the real-world images without ground truth. However, the existing BIQA can only consider an image with a single-distortion-type. For these reasons, a multitask hierarchical blind image quality assessment model is proposed to assess multiple distortion types of images. An integrated algorithm that incorporates an improved deep neural network by introducing a penalty term and a shared layer is proposed to improve its generalization performance. Experimental results show that the proposed algorithm is significantly better than algorithms such as DIIVINE and BRISQUE in the Pearson linear correlation coefficient and Spearman rank-order correlation coefficient; for each image, the three most significant distortion categories and probability results are obtained through the algorithm. It can effectively solve the problem of image quality assessment when multiple types of distortion are present. [ABSTRACT FROM AUTHOR]

The motor-based brain–computer interface is widely used in the exoskeleton reconstruction of patients with muscle weakness and to enhance the operating experience of somatosensory game customers through the combination of actions and electroencephalography signals. However, the recognition algorithms in traditional motor-based brain–computer interfaces have problems such as "brain–computer interface blindness" (recognition accuracy is less than 70%) and "one person one model." In this study, a regularized long short-term memory algorithm and a hardware platform for gesture recognition by using the motor-based brain–computer interface are proposed. Experimental results show that the gesture recognition accuracy rate based on the motor brain–computer interface is up to 95.69%, which is significantly better than that of other algorithms. The proposed model enhances the applicability and generalization ability of the brain–computer interface, for which the practicability and effectiveness are verified. [ABSTRACT FROM AUTHOR]

Imagery-based brain-computer interfaces (BCIs) aim to decode different neural activities into control signals by identifying and classifying various natural commands from electroencephalogram (EEG) patterns and then control corresponding equipment. However, several traditional BCI recognition algorithms have the "one person, one model" issue, where the convergence of the recognition model's training process is complicated. In this study, a new BCI model with a Dense long short-term memory (Dense-LSTM) algorithm is proposed, which combines the event-related desynchronization (ERD) and the event-related synchronization (ERS) of the imagery-based BCI; model training and testing were conducted with its own data set. Furthermore, a new experimental platform was built to decode the neural activity of different subjects in a static state. Experimental evaluation of the proposed recognition algorithm presents an accuracy of 91.56%, which resolves the "one person one model" issue along with the difficulty of convergence in the training process. [ABSTRACT FROM AUTHOR]

This is one of the first reports, which is related to hydrogen production through formic acid decomposition over Pd/ZnO catalysts widely used for methanol steam-reforming. These catalysts have been investigated in comparison with Pt/ZnO and Pd/Al 2 O 3 catalysts as well as ZnO support. HAADF/STEM, XRD, XPS and DRIFTS in situ studies of the systems were performed. The measured catalyst activity corresponds to the following order: Pd/Al 2 O 3 ≥Pd/ZnO > Pt/ZnO > ZnO. Among the studied catalysts, Pd/ZnO showed the highest selectivity to hydrogen (up to 99.3%). This was assigned to the formation of a PdZn alloy during the reductive pre-treatment of the catalyst. An increase of the pre-treatment temperature from 573 to 773 K led to a significant increase of the mean PdZn (PtZn) nanoparticle size. However, the catalyst activity did not change, but the selectivity to hydrogen increased. These features closely remind the behavior of Pd/ZnO catalysts in methanol steam reforming implying that the mechanism of formic acid decomposition involves the same key steps and active sites. [ABSTRACT FROM AUTHOR]

The rapid development of electroplating industries has produced a noticeable amount of electroplating sludge, which may pose serious threat to human health, and required special treatment prior to landfilling. This study developed a novel waste control by waste method for immobilizing electroplating sludge with iron sludge by thermal treatment. Electroplating sludge can be immobilized effectively with iron sludge by transforming heavy metals into spinel structure. Most of heavy metals (Cr, Cu and Zn) would be incorporated in spinel structure when the sintering temperature over 900 °C. The formed spinel crystal was a heterogeneous spinel solid solution, involved ZnCr 2 O 4 , ZnFe 2 O 4 , CuFe 2 O 4 and CuCr 2 O 4 , and their growth rates are as follow: ZnCr 2 O 4 >CuFe 2 O 4 >ZnFe 2 O 4 >CuCr 2 O 4 . ZnCr 2 O 4 would first nucleated and centralized in the central core of the spinel crystal, because its formation is thermodynamically preferable and growth rate is fastest. A prolonged leaching test was carried out to test the leaching risk of heavy metals from the sintered products. The leaching concentrations of heavy metals were below the regulatory limit when the sintering temperature over 1,000 °C. The overall results suggested that it is a promising and reliable strategy to use iron sludge in immobilizing electroplating sludge through incorporating heavy metals into spinel phase. This study also provided a high value-added and sustainable way toward the management of iron-rich waste. [ABSTRACT FROM AUTHOR]

Herein we report the formation of multi-layered arrays of vertically aligned and close packed semiconductor nanorods in perfect registry at a substrate using electric field assisted assembly. The collective properties of these CdSexS1-x nanorod emitters are harnessed by demonstrating a relatively low amplified spontaneous emission (ASE) threshold and a high net optical gain at medium pump intensity. The importance of order in the system is highlighted where a lower ASE threshold is observed compared to disordered samples. [ABSTRACT FROM AUTHOR]

If coated conductors are to be used in large-scale ac applications such as motors and generators, energy losses must be minimised. Hysteretic ac losses can be reduced by dividing the coated conductor into filaments. In this study, a new method for producing filamentary coated conductors is presented. An electrical spark discharge was used to selectively degrade regions of superconducting tape. The robust, noncontact and scalable method was used to striate tapes into four filaments. The filamentary samples had lower ac losses than nonstriated tapes with less than a 7% reduction in current carrying capacity. [ABSTRACT FROM PUBLISHER]

Residual stresses induced during quenching of aluminum alloys cause distortion and have a negative effect on their properties. The purpose of this study is to reduce the residual stresses and improve mechanical properties by using a novel cryogenic treatment. Water quenched samples were cooled down by immersion in liquid nitrogen at −196 °C, following by rapid heating in hot oil at 180 °C and finally they were artificially aged. Residual stresses was measured by the hole drilling strain gauge method. The mechanical properties and microstructure of a heat treated samples were investigated by means of hardness measurements, tensile tests and transmission electron microscopy. The results showed that this treatment can relieve up to 71% of the residual stresses compared to 29% related to the traditional cryogenic treatment that used boiling water as the reheating medium. In addition, there is a considerable increase of about 75 MPa in the ultimate tensile strength in comparison to the T6 heat-treated alloy. TEM observations revealed that the S′ precipitates were fine and uniformly distributed in the microstructure due to deformation during reheating in hot oil. [ABSTRACT FROM AUTHOR]

Despite their large secretome and wide applications in bioprocesses, fungi remain underexplored in metal nanoparticles (MNP) biosynthesis. Previous studies have shown that cell surface proteins of Rhizopus oryzae play a crucial role in biomineralization of Au(III) to produce gold nanoparticles (AuNPs). Therefore, it is hypothesized that purified cell surface protein may produce in vitro AuNPs with narrow size distribution for biomedical and biocatalytic applications. However, different protein extraction methods might affect protein stability and the AuNP biosynthesis process. Herein, we have explored the extraction of cell surface proteins from R. oryzae using common detergents and reducing agent (sodium dodecyl sulfate (SDS) Triton X-100, and 1,4-dithiothreitol (DTT)) and their effect on the size and shape of the biosynthetic AuNPs. The surface proteins extracted with reducing agent (DTT) and non-ionic detergent (Triton X-100) produce spherical AuNPs with a mean particle size of 16 ± 7 nm, and 19 ± 4 nm, respectively, while the AuNPs produced by the surface protein extracted by ionic detergent (SDS) are flower-like AuNPs with broader size distribution of 43 ± 19 nm. This synthetic approach does not require use of any harsh chemicals, multistep preparation and separation process, favouring environmental sustainability. The biosynthetic AuNPs thus formed, are stable in different physiological buffers and hemocompatible, making them suitable for biomedical applications. [ABSTRACT FROM AUTHOR]

Biodegradable strain sensors able to undergo controlled degradation following implantation have recently received significant interest as novel approaches to detect pathological tissue swelling or non-physiological stresses. In this study, the physicomechanical, electrochemical and active pressure sensing behavior of an electrically conductive and biodegradable poly(glycerol sebacate urethane) (PGSU) composite, reinforced with poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) functionalized carbon nanotubes (CNTs), was evaluated in vitro. Analysis of these PGSU-CNTs composites demonstrated that the incorporation of functionalized CNTs into a biodegradable elastomer resulted in enhanced mechanical strength, conductivity and tailored matrix biodegradation. PGSU-CNT composites were subsequently formulated into flexible and active pressure sensors which demonstrated optimal sensitivity to applied 1% uniaxial tensile strains. Finally, cytocompatibility analysis a with primary neural culture confirmed that PGSU-CNT composites exhibited low cytotoxicity, and supported neuron adhesion, viability, and proliferation in vitro. Unlabelled Image • Functionalized CNTs network improved electrical and mechanical properties of polymer. • A biodegradable strain sensor was formulated from a PGSU-CNT nanocomposite. • PGSU-CNTs nanocomposite showed optimal sensitivity to 1% uniaxial tensile strain. • PGSU-CNT was shown to support the adhesion of neural cells. • The material was observed to undergo hydrolysis with a controlled degradation rate. [ABSTRACT FROM AUTHOR]