scholarly journals Micro-scale Realization of Compliant Mechanisms: Manufacturing Processes and Constituent Materials—A Review

2021 ◽  
Vol 34 (1) ◽  
Author(s):  
Minchang Wang ◽  
Daohan Ge ◽  
Liqiang Zhang ◽  
Just L. Herder
Keyword(s):  
3D Printing ◽  
Compliant Mechanisms ◽  
State Of The Art ◽  
Manufacturing Processes ◽  
Mems Devices ◽  
Process Selection ◽  
Micro Scale ◽  
Great Progress ◽  
Different Types ◽  
Made In

AbstractCompliant micromechanisms (CMMs) acquire mobility from the deflection of elastic members and have been proven to be robust by millions of silicon MEMS devices. However, the limited deflection of silicon impedes the realization of more sophisticated CMMs, which often require larger deflections. Recently, some novel manufacturing processes have emerged but are not well known by the community. In this paper, the realization of CMMs is reviewed, aiming to provide help to mechanical designers to quickly find the proper realization method for their CMM designs. To this end, the literature surveyed was classified and statistically analyzed, and representative processes were summarized individually to reflect the state of the art of CMM manufacturing. Furthermore, the features of each process were collected into tables to facilitate the reference of readers, and the guidelines for process selection were discussed. The review results indicate that, even though the silicon process remains dominant, great progress has been made in the development of polymer-related and composite-related processes, such as micromolding, SU-8 process, laser ablation, 3D printing, and the CNT frameworking. These processes result in constituent materials with a lower Young’s modulus and larger maximum allowable strain than silicon, and therefore allow larger deflection. The geometrical capabilities (e.g., aspect ratio) of the realization methods should also be considered, because different types of CMMs have different requirements. We conclude that the SU-8 process, 3D printing, and carbon nanotube frameworking will play more important roles in the future owing to their excellent comprehensive capabilities.

scholarly journals Short-time speaker verification with different speaking style utterances

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0241809
Author(s):  
Hongwei Mao ◽  
Yan Shi ◽  
Yue Liu ◽  
Linqiang Wei ◽  
Yijie Li ◽  
...  
Keyword(s):  
State Of The Art ◽  
Speaker Verification ◽  
Feature Space ◽  
Gaussian Mixture ◽  
Normal Reading ◽  
Great Progress ◽  
Short Time ◽  
Speaking Style ◽  
Target Speaker ◽  
Made In

In recent years, great progress has been made in the technical aspects of automatic speaker verification (ASV). However, the promotion of ASV technology is still a very challenging issue, because most technologies are still very sensitive to new, unknown and spoofing conditions. Most previous studies focused on extracting target speaker information from natural speech. This paper aims to design a new ASV corpus with multi-speaking styles and investigate the ASV robustness to these different speaking styles. We first release this corpus in the Zenodo website for public research, in which each speaker has several text-dependent and text-independent singing, humming and normal reading speech utterances. Then, we investigate the speaker discrimination of each speaking style in the feature space. Furthermore, the intra and inter-speaker variabilities in each different speaking style and cross-speaking styles are investigated in both text-dependent and text-independent ASV tasks. Conventional Gaussian Mixture Model (GMM), and the state-of-the-art x-vector are used to build ASV systems. Experimental results show that the voiceprint information in humming and singing speech are more distinguishable than that in normal reading speech for conventional ASV systems. Furthermore, we find that combing the three speaking styles can significantly improve the x-vector based ASV system, even when only limited gains are obtained by conventional GMM-based systems.

scholarly journals Temperature-Dependent Photoluminescent Properties of PbSe Nanoplatelets

Nanomaterials ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 2570
Author(s):  
Ivan Skurlov ◽  
Anastasiia Sokolova ◽  
Tom Galle ◽  
Sergei Cherevkov ◽  
Elena Ushakova ◽  
...  
Keyword(s):  
Near Infrared ◽  
State Of The Art ◽  
Visible Spectral Range ◽  
Visible Range ◽  
Temperature Dependent ◽  
Research Attention ◽  
Light Emitting ◽  
New Class ◽  
Great Progress ◽  
Made In

Semiconductor colloidal nanoplatelets (NPLs) are a promising new class of nanostructures that can bring much impact on lightning technologies, light-emitting diodes (LED), and laser fabrication. Indeed, great progress has been made in optimizing the optical properties of the NPLs for the visible spectral range, which has already made the implementation of a number of effective devices on their basis possible. To date, state-of-the-art near-infrared (NIR)-emitting NPLs are significantly inferior to their visible-range counterparts, although it would be fair to say that they received significantly less research attention so far. In this study, we report a comprehensive analysis of steady-state and time-dependent photoluminescence (PL) properties of four monolayered (ML) PbSe NPLs. The PL measurements are performed in a temperature range of 78–300 K, and their results are compared to those obtained for CdSe NPLs and PbSe quantum dots (QDs). We show that multiple emissive states, both band-edge and trap-related, are responsible for the formation of the NPLs’ PL band. We demonstrate that the widening of the PL band is caused by the inhomogeneous broadening rather than homogeneous one, and analyze the possible contributions to PL broadening.

scholarly journals Diagnostic Value of the Fimbriae Distribution Pattern in Localization of Urinary Tract Infection

2021 ◽  
Vol 8 ◽  
Author(s):  
Xiao Li ◽  
Kaichen Zhou ◽  
Jingyu Wang ◽  
Jiahe Guo ◽  
Yang Cao ◽  
...  
Keyword(s):  
Urinary Tract ◽  
Operating Characteristic ◽  
Area Under The Curve ◽  
Distribution Patterns ◽  
Diagnostic Value ◽  
Specific Attachment ◽  
Great Progress ◽  
Different Types ◽  
Tract Infections ◽  
Made In

Urinary tract infections (UTIs) are one of the most common infectious diseases. UTIs are mainly caused by uropathogenic Escherichia coli (UPEC), and are either upper or lower according to the infection site. Fimbriae are necessary for UPEC to adhere to the host uroepithelium, and are abundant and diverse in UPEC strains. Although great progress has been made in determining the roles of different types of fimbriae in UPEC colonization, the contributions of multiple fimbriae to site-specific attachment also need to be considered. Therefore, the distribution patterns of 22 fimbrial genes in 90 UPEC strains from patients diagnosed with upper or lower UTIs were analyzed using PCR. The distribution patterns correlated with the infection sites, an XGBoost model with a mean accuracy of 83.33% and a mean area under the curve (AUC) of the receiver operating characteristic (ROC) of 0.92 demonstrated that fimbrial gene distribution patterns could predict the localization of upper and lower UTIs.

Noise properties of thin-film Ni-P resistors embedded in printed circuit boards

2013 ◽  
Vol 61 (3) ◽  
pp. 731-735
Author(s):  
A.W. Stadler ◽  
Z. Zawiślak ◽  
W. Stęplewski ◽  
A. Dziedzic
Keyword(s):  
Thin Film ◽  
Printed Circuit Boards ◽  
Circuit Boards ◽  
Noise Component ◽  
Printed Circuit ◽  
Resistance Bridge ◽  
Different Types ◽  
Signal Path ◽  
Resistance Fluctuations ◽  
Made In

Abstract. Noise studies of planar thin-film Ni-P resistors made in/on Printed Circuit Boards, both covered with two different types of cladding or uncladded have been described. The resistors have been made of the resistive-conductive-material (Ohmega-Ply©) of 100 Ώ/sq. Noise of the selected pairs of samples has been measured in the DC resistance bridge with a transformer as the first stage in a signal path. 1/f noise caused by resistance fluctuations has been found to be the main noise component. Parameters describing noise properties of the resistors have been calculated and then compared with the parameters of other previously studied thin- and thick-film resistive materials.

Biological Production of (S)-acetoin: A State-of-the-Art Review

2019 ◽  
Vol 19 (25) ◽  
pp. 2348-2356 ◽  
Author(s):  
Neng-Zhong Xie ◽  
Jian-Xiu Li ◽  
Ri-Bo Huang
Keyword(s):  
Side Effects ◽  
Chemical Synthesis ◽  
State Of The Art ◽  
Optically Active ◽  
Considerable Progress ◽  
Future Prospects ◽  
Chiral Compound ◽  
Biological Production ◽  
Acetoin Production ◽  
Made In

Acetoin is an important four-carbon compound that has many applications in foods, chemical synthesis, cosmetics, cigarettes, soaps, and detergents. Its stereoisomer (S)-acetoin, a high-value chiral compound, can also be used to synthesize optically active drugs, which could enhance targeting properties and reduce side effects. Recently, considerable progress has been made in the development of biotechnological routes for (S)-acetoin production. In this review, various strategies for biological (S)- acetoin production are summarized, and their constraints and possible solutions are described. Furthermore, future prospects of biological production of (S)-acetoin are discussed.

scholarly journals Multiple objects tracking in the UAV system based on hierarchical deep high-resolution network

2021 ◽  
Author(s):  
Wei Huang ◽  
Xiaoshu Zhou ◽  
Mingchao Dong ◽  
Huaiyu Xu
Keyword(s):  
High Resolution ◽  
Object Tracking ◽  
High Performance ◽  
State Of The Art ◽  
Class Imbalance ◽  
Unified Framework ◽  
Multiple Objects ◽  
Tracking Process ◽  
Objects Tracking ◽  
Different Types

AbstractRobust and high-performance visual multi-object tracking is a big challenge in computer vision, especially in a drone scenario. In this paper, an online Multi-Object Tracking (MOT) approach in the UAV system is proposed to handle small target detections and class imbalance challenges, which integrates the merits of deep high-resolution representation network and data association method in a unified framework. Specifically, while applying tracking-by-detection architecture to our tracking framework, a Hierarchical Deep High-resolution network (HDHNet) is proposed, which encourages the model to handle different types and scales of targets, and extract more effective and comprehensive features during online learning. After that, the extracted features are fed into different prediction networks for interesting targets recognition. Besides, an adjustable fusion loss function is proposed by combining focal loss and GIoU loss to solve the problems of class imbalance and hard samples. During the tracking process, these detection results are applied to an improved DeepSORT MOT algorithm in each frame, which is available to make full use of the target appearance features to match one by one on a practical basis. The experimental results on the VisDrone2019 MOT benchmark show that the proposed UAV MOT system achieves the highest accuracy and the best robustness compared with state-of-the-art methods.

scholarly journals Pathogenesis and Potential Therapeutic Targets for Triple-Negative Breast Cancer

Cancers ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 2978
Author(s):  
Chia-Jung Li ◽  
Yen-Dun Tony Tzeng ◽  
Yi-Han Chiu ◽  
Hung-Yu Lin ◽  
Ming-Feng Hou ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Targeted Therapy ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
High Efficiency ◽  
Early Recurrence ◽  
New Developments ◽  
Great Progress ◽  
Low Toxicity ◽  
Made In

Triple negative breast cancer (TNBC) is a heterogeneous tumor characterized by early recurrence, high invasion, and poor prognosis. Currently, its treatment includes chemotherapy, which shows a suboptimal efficacy. However, with the increasing studies on TNBC subtypes and tumor molecular biology, great progress has been made in targeted therapy for TNBC. The new developments in the treatment of breast cancer include targeted therapy, which has the advantages of accurate positioning, high efficiency, and low toxicity, as compared to surgery, radiotherapy, and chemotherapy. Given its importance as cancer treatment, we review the latest research on the subtypes of TNBC and relevant targeted therapies.

scholarly journals Downregulation of exosomal let-7d and miR-16 in idiopathic pulmonary fibrosis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Donato Lacedonia ◽  
Giulia Scioscia ◽  
Piera Soccio ◽  
Massimo Conese ◽  
Lucia Catucci ◽  
...  
Keyword(s):  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Therapy Response ◽  
Down Regulation ◽  
Cross Sectional ◽  
Exosomal Mirnas ◽  
Different Types ◽  
Sectional Analysis ◽  
Made In

Abstract Background Idiopathic Pulmonary Fibrosis (IPF) is a degenerative interstitial lung disease with both a poor prognosis and quality of life once the diagnosis is made. In the last decade many features of the disease have been investigated to better understand the pathological steps that lead to the onset of the disease and, moreover, different types of biomarkers have been tested to find valid diagnostic, prognostic and therapy response predictive ones. In the complexity of IPF, microRNA (miRNAs) biomarker investigation seems to be promising. Methods We analysed the expression of five exosomal miRNAs supposed to have a role in the pathogenesis of the disease from serum of a group of IPF patients (n = 61) and we compared it with the expression of the same miRNAs in a group of healthy controls (n = 15). Results In the current study what emerged is let-7d down-regulation and, unexpectedly, miR-16 significant down-regulation. Moreover, through a cross-sectional analysis, a clustering of the expression of miR-16, miR-21 and miR-26a was found. Conclusions These findings could help the individuation of previously unknown key players in the pathophysiology of IPF and, most interestingly, more specific targets for the development of effective medications.

scholarly journals Fighting Together against the Pandemic: Learning Multiple Models on Tomography Images for COVID-19 Diagnosis

AI ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 261-273
Author(s):  
Mario Manzo ◽  
Simone Pellino
Keyword(s):  
Network Architecture ◽  
State Of The Art ◽  
Ensemble Classification ◽  
Effective Vaccine ◽  
Rt Pcr ◽  
Neural Network Architecture ◽  
Experimental Phase ◽  
Different Types ◽  
Polymerase Chain ◽  
Better Than

COVID-19 has been a great challenge for humanity since the year 2020. The whole world has made a huge effort to find an effective vaccine in order to save those not yet infected. The alternative solution is early diagnosis, carried out through real-time polymerase chain reaction (RT-PCR) tests or thorax Computer Tomography (CT) scan images. Deep learning algorithms, specifically convolutional neural networks, represent a methodology for image analysis. They optimize the classification design task, which is essential for an automatic approach with different types of images, including medical. In this paper, we adopt a pretrained deep convolutional neural network architecture in order to diagnose COVID-19 disease from CT images. Our idea is inspired by what the whole of humanity is achieving, as the set of multiple contributions is better than any single one for the fight against the pandemic. First, we adapt, and subsequently retrain for our assumption, some neural architectures that have been adopted in other application domains. Secondly, we combine the knowledge extracted from images by the neural architectures in an ensemble classification context. Our experimental phase is performed on a CT image dataset, and the results obtained show the effectiveness of the proposed approach with respect to the state-of-the-art competitors.

Rhodium-Catalyzed, Phosphorus(III)-Directed Hydroarylation of Internal Alkynes: Facile and Efficient Access to New Phosphine Ligands

Synlett ◽  
2020 ◽  
Author(s):  
Minyan Wang ◽  
Zhuangzhi Shi ◽  
Huanhuan Luo ◽  
Dawei Wang
Keyword(s):  
High Selectivity ◽  
Enantiomeric Excess ◽  
Phosphine Ligands ◽  
Rapid Construction ◽  
Efficient Access ◽  
Internal Alkynes ◽  
Great Progress ◽  
Chiral Phosphine Ligands ◽  
Optimized Conditions ◽  
Made In

AbstractOrganophosphines are an important class of ligands widely used in organic chemistry. Although great progress has recently been made in the rapid construction of new phosphines through Rh- or Ru-catalyzed C–H bond functionalizations, synthetic access to more diverse phosphines remains a challenge. We describe an efficient process for the rhodium-catalyzed phosphorus(III)-directed hydroarylation of internal alkynes to generate various alkenylated and 2′,6′-dialkenylated biarylphosphines with high selectivity. A range of diverse alkynes and phosphines were effectively prepared with broad functional-group compatibility under the optimized conditions. In addition, the developed protocol can be extended to modify chiral phosphine ligands, providing enantioenriched alkenylated phosphines without erosion of the enantiomeric excess.

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