TiNi intermetallic alloys were prepared with 2, 4 and 6 at.% niobium (Nb) addition. The mechanical properties and microstructures of the alloys were investigated under both static (1 × 10
to 1 × 10
s
...) and dynamic (4 × 10
to 6 × 10
s
) loading conditions. The intermetallic alloy structures and surface morphologies of the alloys were examined by X-ray diffraction (XRD) and scanning electron microscopy (SEM), respectively. In addition, the fracture morphologies were observed by optical microscopy (OM). It was shown that the addition of 2 to 4 at.% Nb increased the strength of the TiNi alloy. However, as the level of Nb addition was further increased to 6 at.%, a significant reduction in strength occurred. For a constant Nb addition, the plastic flow stress and strain rate sensitivity increased with increasing strain rate under both loading conditions (static and dynamic). The XRD and SEM results showed that the original surface morphologies were composed primarily of dendritic structures and fine β-Nb + TiNi eutectic systems. Moreover, the OM results showed that the alloys underwent a transition from a brittle fracture mode to a ductile fracture mode as the level of Nb addition increased.
Purpose
Gamma Knife radiosurgery (GKRS) is a non-invasive procedure for the treatment of brain metastases. This study sought to determine whether radiomic features of brain metastases derived from ...pre-GKRS magnetic resonance imaging (MRI) could be used in conjunction with clinical variables to predict the effectiveness of GKRS in achieving local tumor control.
Methods
We retrospectively analyzed 161 patients with non-small cell lung cancer (576 brain metastases) who underwent GKRS for brain metastases. The database included clinical data and pre-GKRS MRI. Brain metastases were demarcated by experienced neurosurgeons, and radiomic features of each brain metastasis were extracted. Consensus clustering was used for feature selection. Cox proportional hazards models and cause-specific proportional hazards models were used to correlate clinical variables and radiomic features with local control of brain metastases after GKRS.
Results
Multivariate Cox proportional hazards model revealed that higher zone percentage (hazard ratio, HR 0.712;
P
= .022) was independently associated with superior local tumor control. Similarly, multivariate cause-specific proportional hazards model revealed that higher zone percentage (HR 0.699;
P
= .014) was independently associated with superior local tumor control.
Conclusions
The zone percentage of brain metastases, a radiomic feature derived from pre-GKRS contrast-enhanced T1-weighted MRIs, was found to be an independent prognostic factor of local tumor control following GKRS in patients with non-small cell lung cancer and brain metastases. Radiomic features indicate the biological basis and characteristics of tumors and could potentially be used as surrogate biomarkers for predicting tumor prognosis following GKRS.
Given the significant proportion of the outsourced parts, components, and the complex assembly structure of the automobiles, agriculture machinery and heavy industry equipment, distributed production ...and flexible assembly are much-needed production scheduling settings to optimise their global supply chains. This research extends the distributed assembly permutation flowshop scheduling problem to account for flexible assembly and sequence-independent setup times (DPFSP_FAST) in a supply chain-like setting. For this purpose, an original mixed-integer linear programming (MILP) formulation to the DPFSP_FAST problem is first investigated. Considering makespan as the optimisation criterion, constructive heuristic and customised metaheuristic algorithms are then proposed to solve this emerging scheduling extension. Through extensive computational experiments, it is shown that the proposed algorithms outperform the existing best-performing algorithms to solve the DPFSP_FAST problem, yielding the best-found solutions in nearly all of the benchmark instances. Narrowing the gap between theory and practice, this study helps integrate the production planning scheduling across the supply chain.
Objective: In a cochlear implant (CI) speech processor, noise reduction (NR) is a critical component for enabling CI users to attain improved speech perception under noisy conditions. Identifying an ...effective NR approach has long been a key topic in CI research. Method: Recently, a deep denoising autoencoder (DDAE) based NR approach was proposed and shown to be effective in restoring clean speech from noisy observations. It was also shown that DDAE could provide better performance than several existing NR methods in standardized objective evaluations. Following this success with normal speech, this paper further investigated the performance of DDAE-based NR to improve the intelligibility of envelope-based vocoded speech, which simulates speech signal processing in existing CI devices. Results: We compared the performance of speech intelligibility between DDAE-based NR and conventional single-microphone NR approaches using the noise vocoder simulation. The results of both objective evaluations and listening test showed that, under the conditions of nonstationary noise distortion, DDAE-based NR yielded higher intelligibility scores than conventional NR approaches. Conclusion and significance: This study confirmed that DDAE-based NR could potentially be integrated into a CI processor to provide more benefits to CI users under noisy conditions.
Twisting between two stacked monolayers modulates periodic potentials and forms the Moiré electronic superlattices, which offers an additional degree of freedom to alter material property. ...Considerable unique observations, including unconventional superconductivity, coupled spin‐valley states, and quantized interlayer excitons are correlated to the electronic superlattices but further study requires reliable routes to study the Moiré in real space. Scanning tunneling microscopy (STM) is ideal to precisely probe the Moiré superlattice and correlate coupled parameters among local electronic structures, strains, defects, and band alignment at atomic scale. Here, a clean route is developed to construct twisted lattices using synthesized monolayers for fundamental studies. Diverse Moiré superlattices are predicted and successfully observed with STM at room temperature. Electrical tuning of the Moiré superlattice is achieved with stacked TMD on graphite.
Ultraclean transfer of synthesized monolayers is developed for artificially stacked monolayers with tunable twisting and a hetero‐interface. Diverse Moiré electronic superlattices are directly visualized and studied with scanning tunneling microscopy (STM), which will open up opportunities for diverse correlated properties in artificial 2D lattices.
Speech enhancement (SE) aims to reduce noise in speech signals. Most SE techniques focus only on addressing audio information. In this paper, inspired by multimodal learning, which utilizes data from ...different modalities, and the recent success of convolutional neural networks (CNNs) in SE, we propose an audio-visual deep CNNs (AVDCNN) SE model, which incorporates audio and visual streams into a unified network model. We also propose a multitask learning framework for reconstructing audio and visual signals at the output layer. Precisely speaking, the proposed AVDCNN model is structured as an audio-visual encoder-decoder network, in which audio and visual data are first processed using individual CNNs, and then fused into a joint network to generate enhanced speech (the primary task) and reconstructed images (the secondary task) at the output layer. The model is trained in an end-to-end manner, and parameters are jointly learned through back propagation. We evaluate enhanced speech using five instrumental criteria. Results show that the AVDCNN model yields a notably superior performance compared with an audio-only CNN-based SE model and two conventional SE approaches, confirming the effectiveness of integrating visual information into the SE process. In addition, the AVDCNN model also outperforms an existing audio-visual SE model, confirming its capability of effectively combining audio and visual information in SE.
Electrocardiogram (ECG)-based intelligent screening for systolic heart failure (HF) is an emerging method that could become a low-cost and rapid screening tool for early diagnosis of the disease ...before the comprehensive echocardiographic procedure. We collected 12-lead ECG signals from 900 systolic HF patients (ejection fraction, EF < 50%) and 900 individuals with normal EF in the absence of HF symptoms. The 12-lead ECG signals were converted by continuous wavelet transform (CWT) to 2D spectra and classified using a 2D convolutional neural network (CNN). The 2D CWT spectra of 12-lead ECG signals were trained separately in 12 identical 2D-CNN models. The 12-lead classification results of the 2D-CNN model revealed that Lead V6 had the highest accuracy (0.93), sensitivity (0.97), specificity (0.89), and f1 scores (0.94) in the testing dataset. We designed four comprehensive scoring methods to integrate the 12-lead classification results into a key diagnostic index. The highest quality result among these four methods was obtained when Leads V5 and V6 of the 12-lead ECG signals were combined. Our new 12-lead ECG signal-based intelligent screening method using straightforward combination of ECG leads provides a fast and accurate approach for pre-screening for systolic HF.
Objective: This study focuses on the first (S1) and second (S2) heart sound recognition based only on acoustic characteristics; the assumptions of the individual durations of S1 and S2 and time ...intervals of S1-S2 and S2-S1 are not involved in the recognition process. The main objective is to investigate whether reliable S1 and S2 recognition performance can still be attained under situations where the duration and interval information might not be accessible. Methods: A deep neural network (DNN) method is proposed for recognizing S1 and S2 heart sounds. In the proposed method, heart sound signals are first converted into a sequence of Mel-frequency cepstral coefficients (MFCCs). The K-means algorithm is applied to cluster MFCC features into two groups to refine their representation and discriminative capability. The refined features are then fed to a DNN classifier to perform S1 and S2 recognition. We conducted experiments using actual heart sound signals recorded using an electronic stethoscope. Precision, recall, F-measure, and accuracy are used as the evaluation metrics. Results: The proposed DNN-based method can achieve high precision, recall, and F-measure scores with more than 91% accuracy rate. Conclusion: The DNN classifier provides higher evaluation scores compared with other well-known pattern classification methods. Significance: The proposed DNN-based method can achieve reliable S1 and S2 recognition performance based on acoustic characteristics without using an ECG reference or incorporating the assumptions of the individual durations of S1 and S2 and time intervals of S1-S2 and S2-S1.
IMP‐3 expression is a poor prognostic factor of melanomas and it promotes melanoma cell migration and invasion by a pathway modulating HMGA2 mRNA expression. We tried to identify other putative ...targets of IMP‐3. We identified putative IMP‐3‐binding RNAs, including AKT1, MAPK3, RB1 and RELA, by RNA immunoprecipitation coupled with next‐generation sequencing. IMP‐3 overexpression increased AKT and RELA levels in MeWo cells. siRNAs against AKT1 and RELA inhibited MeWo/Full‐length IMP‐3 cell migration. IMP‐3 knockdown of A2058 cells decreased AKT1 and RELA expression and lowered migration ability. Co‐transfection of A2058 cells with AKT1‐ or RELA‐expressing plasmids with IMP‐3 siRNA restored the inhibitory effects of IMP‐3 knockdown on migration. HMGA2 did not influence AKT1 and RELA expression in melanoma cells. Human melanoma samples with high IMP‐3 levels also showed high HMGA2, AKT1 and RELA expression. Our results show that IMP‐3 enhances melanoma cell migration through the regulation of the AKT1 and RELA axis.
Infections caused by enterohemorrhagic Escherichia coli (EHEC) can lead to diarrhea with abdominal cramps and sometimes are complicated by severe hemolytic uremic syndrome. EHEC secretes effector ...proteins into host cells through a type III secretion system that is composed of proteins encoded by a chromosomal island, locus for the enterocyte effacement (LEE). EspA is the major component of the filamentous structure connecting the bacteria and the host's cells. Synthesis and secretion of EspA must be carefully controlled since the protein is prone to polymerize. CesAB, CesA2, and EscL have been identified as being able to interact with EspA. Furthermore, the intracellular level of EspA declines when cesAB, cesA2, and escL are individually deleted. Here, we report a LEE gene named l0033, which also affects the intracellular level of EspA. We renamed l0033 as escA since its counterpart in enteropathogenic E. coli has been recently described. Similar to CesAB, EscL, and CesA2, EscA interacts with EspA and enhances the protein stability of EspA. However, EscA is also able to interact with inner membrane-associated EscL, CesA2, and EscN, but not with cytoplasmic CesAB. In terms of gene organizations, escA locates in LEE3. Expression of EscA is faithfully regulated via Mpc, the first gene product of LEE3. Since Mpc is tightly regulated to low level, we suggest that EscA is highly synchronized and critical to the process of escorting EspA to its final destination.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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